黑马Python6.0人工智能全套课程-全新升级（完整资料）
从基础到实战，全面掌握运维技能
编辑点评
深入浅出讲解运维知识，涵盖Apache、Keepalived、Nagios、Shell脚本等多个实战项目，助你快速提升运维技能。
⭐ 编辑推荐
本课程全面涵盖Python运维技能，从基础到实战，助你成为优秀的运维工程师。
课程亮点
• Python运维全栈知识
• 实战项目丰富
• 深入浅出教学
课程目录
📁 13运维
📁 08_apache安装和配置
001-apache概述安装-.mp4 [37.6 MB]
002-apache配置服务路劲认识-.mp4 [7.9 MB]
010-配置详解总结-.mp4 [14.6 MB]
009-配置详解6-.mp4 [38.5 MB]
003-apache基本概念-.mp4 [20.9 MB]
008-配置详解5-.mp4 [56.7 MB]
007-配置详解4-.mp4 [34.5 MB]
004-配置详解1-.mp4 [30.8 MB]
005-配置详解2-.mp4 [28.4 MB]
📁 26keepalived 集群基础
002_集群基础之集群简介(可用性指标)-.mp4 [47.7 MB]
001_集群基础之集群简介(集群分类)-.mp4 [18.7 MB]
003_集群基础之集群简介(高可用方式)-.mp4 [42.6 MB]
000_课程概况-.mp4 [4.2 MB]
📁 43nagios简介和部署
012_快速入门之nagios部署(启动服务)-.mp4 [14.0 MB]
013_快速入门之nagios部署(界面效果)-.mp4 [18.1 MB]
007_快速入门之nagios部署(准备环境)-.mp4 [25.1 MB]
004_快速入门之nagios简介(基础知识)-.mp4 [23.4 MB]
008_快速入门之nagios部署(web环境1)-.mp4 [41.3 MB]
011_快速入门之nagios部署(插件安装)-.mp4 [46.3 MB]
010_快速入门之nagios部署(nagios安装)-.mp4 [52.2 MB]
006_快速入门之nagios简介(部署原理)-.mp4 [25.2 MB]
005_快速入门之nagios简介(特点)-.mp4 [17.5 MB]
009_快速入门之nagios部署(web环境2)-.mp4 [29.3 MB]
📁 12_shell核心知识表达式
015_核心知识之表达式(数组-简介+定义+查看)-.mp4 [27.0 MB]
012_核心知识之表达式(条件表达式-逻辑+文件)-.mp4 [24.8 MB]
014_核心知识之表达式(计算表达式-场景+格式+实践)-.mp4 [14.9 MB]
016_核心知识之表达式(数组-增删改查)-.mp4 [26.8 MB]
011_核心知识之表达式(测试语句-应用场景+语句格式)-.mp4 [14.7 MB]
013_核心知识之表达式(条件表达式-数字+字符串)-.mp4 [14.8 MB]
📁 37playbook任务依赖和标签
047_快速入门之playbook(标签2)-.mp4 [41.4 MB]
045_快速入门之playbook(任务依赖2)-.mp4 [29.9 MB]
046_快速入门之playbook(标签1)-.mp4 [28.7 MB]
043_快速入门之playbook(异常中断)-.mp4 [46.6 MB]
044_快速入门之playbook(任务依赖1)-.mp4 [29.2 MB]
📁 25LVS TUN实践
043_lvs快速入门之TUN实践(原理详解)-.mp4 [22.8 MB]
040_lvs快速入门之TUN实践(简单实践1)-.mp4 [19.5 MB]
044_lvs快速入门之小结-.mp4 [20.9 MB]
038_lvs快速入门之TUN实践(隧道实践)-.mp4 [51.3 MB]
042_lvs快速入门之TUN实践(简单实践3)-.mp4 [27.0 MB]
039_lvs快速入门之TUN实践(TUN简介)-.mp4 [16.8 MB]
036_lvs快速入门之TUN实践(前置知识)-.mp4 [30.3 MB]
037_lvs快速入门之TUN实践(前置知识2)-.mp4 [9.9 MB]
041_lvs快速入门之TUN实践(简单实践2)-.mp4 [28.7 MB]
📁 10_运维和shell脚本
000_课程概况-.mp4 [6.2 MB]
003_shell基础之shell脚本(创建脚本-方式+命名+内容+注释)-.mp4 [18.2 MB]
004_shell基础之shell脚本(脚本使用-执行方式+开发规范)-.mp4 [32.9 MB]
001_shell基础之运维&shell(运维基础-运维定位+工作范围+运维&shell)-.mp4 [16.6 MB]
002_shell基础之运维&shell(shell简介-shell定位+shell分类+使用方式)-.mp4 [22.1 MB]
📁 30keepalived 配置详解2
027_快速入门之配置详解(日志配置)-.mp4 [45.0 MB]
022_快速入门之配置详解(虚拟主机配置)-.mp4 [43.6 MB]
026_快速入门之配置详解(友情提示)-.mp4 [42.8 MB]
028_快速入门之配置详解(小结)-.mp4 [23.7 MB]
023_快速入门之配置详解(状态健康检测1)-.mp4 [37.6 MB]
025_快速入门之配置详解(TCP状态健康检测)-.mp4 [35.0 MB]
024_快速入门之配置详解(状态健康检测2)-.mp4 [18.3 MB]
📁 27keepalived 软件基础
007_快速入门之软件基础(VRRP)-.mp4 [25.3 MB]
005_快速入门之软件基础(软件结构)-.mp4 [34.1 MB]
006_快速入门之软件基础(LVS)-.mp4 [26.2 MB]
004_快速入门之软件基础(keepalived)-.mp4 [20.4 MB]
📁 18iptables快速入门之匹配
022_iptables快速入门之规则进阶(普通匹配1-目标地址实践)-.mp4 [27.3 MB]
025_iptables快速入门之规则进阶(扩展匹配-端口扩展实践)-.mp4 [48.3 MB]
026_iptables快速入门之规则进阶(扩展匹配-地址扩展实践)-.mp4 [28.6 MB]
020_iptables快速入门之规则进阶(普通匹配1-匹配条件详解)-.mp4 [24.7 MB]
024_iptables快速入门之规则进阶(扩展匹配-扩展简介+扩展分类)-.mp4 [24.1 MB]
021_iptables快速入门之规则进阶(普通匹配1-多目标实践)-.mp4 [43.5 MB]
023_iptables快速入门之规则进阶(普通匹配2-协议实践+接口实践)-.mp4 [53.5 MB]
📁 45nagios配置详解2
022_快速入门之配置详解(http实践1)-.mp4 [44.2 MB]
024_快速入门之配置详解(http实践3)-.mp4 [29.0 MB]
027_快速入门之配置详解(邮件告警2)-.mp4 [40.0 MB]
026_快速入门之配置详解(邮件告警1)-.mp4 [37.9 MB]
023_快速入门之配置详解(http实践2)-.mp4 [23.4 MB]
028_快速入门之配置详解(配置角色)-.mp4 [23.2 MB]
025_快速入门之配置详解(告警配置)-.mp4 [38.7 MB]
📁 16iptables快速入门之日常操作
009_iptables快速入门之日常操作(firewall快速入门)-.mp4 [37.7 MB]
011_iptables快速入门之日常操作(简单实践-增删改查)-.mp4 [70.1 MB]
013_iptables快速入门之日常操作(规则实践-增+删+改)-.mp4 [51.5 MB]
012_iptables快速入门之日常操作(规则简介-定义+简介+格式+动作)-.mp4 [42.6 MB]
010_iptables快速入门之日常操作(iptables快速入门)-.mp4 [21.0 MB]
008_快速入门之iptables简介(基础-结构+关联)-.mp4 [24.5 MB]
📁 41ansible进阶之Role
067_ansible进阶之Role(简单案例1)-.mp4 [29.0 MB]
072_ansible进阶之Role(扩展功能1)-.mp4 [22.1 MB]
079_第四天总结-.mp4 [24.8 MB]
078_ansible进阶之Role(综合实践4)-.mp4 [36.9 MB]
075_ansible进阶之Role(综合实践)-.mp4 [20.6 MB]
070_ansible进阶之Role(role结构)-.mp4 [16.3 MB]
068_ansible进阶之Role(简单案例2)-.mp4 [47.9 MB]
073_ansible进阶之Role(扩展功能2)-.mp4 [46.4 MB]
076_ansible进阶之Role(综合实践2)-.mp4 [40.8 MB]
071_ansible进阶之Role(角色管理)-.mp4 [36.3 MB]
066_ansible进阶之Role(角色基础)-.mp4 [28.1 MB]
069_ansible进阶之Role(简单案例3)-.mp4 [5.6 MB]
074_ansible进阶之Role(扩展功能3)-.mp4 [14.8 MB]
📁 31项目管理基础
002_项目管理基础之项目环境(平台环境)-.mp4 [32.8 MB]
004_项目管理基础之项目管理(管理方式)-.mp4 [26.7 MB]
003_项目管理基础之项目环境(项目环境)-.mp4 [14.5 MB]
006_项目管理基础之项目管理(工具模式)-.mp4 [21.9 MB]
001_项目管理基础之项目环境(项目基础)-.mp4 [42.7 MB]
005_项目管理基础之项目管理(管理工具)-.mp4 [13.1 MB]
000_课程概况-.mp4 [6.7 MB]
📁 22LVS快速入门
008_lvs快速入门之lvs快速入门(主机命令-查看+增加+编辑+删除)-.mp4 [37.2 MB]
004_lvs快速入门之lvs基础(防火墙回顾-五表五链+应用场景+地址转换)-.mp4 [23.6 MB]
009_lvs快速入门之lvs快速入门(规则命令-保存+清空+载入+服务)-.mp4 [45.5 MB]
005_lvs快速入门之lvs基础(简介-结构)-.mp4 [55.2 MB]
007_lvs快速入门之lvs快速入门(集群命令-查看+增加+编辑+删除)-.mp4 [26.8 MB]
010_lvs快速入门之lvs快速入门(小结)-.mp4 [13.5 MB]
006_lvs快速入门之lvs快速入门(安装软件-命令简介)-.mp4 [30.1 MB]
📁 05_用户、组和权限管理
013-用户与组-组管理-.mp4 [12.0 MB]
016-权限管理-数字形式设置权限-.mp4 [26.5 MB]
012-用户与组-删除用户-.mp4 [18.0 MB]
010-用户与组-创建用户-.mp4 [17.6 MB]
011-用户与组-设置密码修改用户信息-.mp4 [23.0 MB]
009-用户与组-介绍-.mp4 [5.4 MB]
014-权限管理-权限概述查看权限-.mp4 [19.7 MB]
017-权限管理-所有者和所属组管理-.mp4 [10.4 MB]
018-权限管理-umask默认权限-.mp4 [16.1 MB]
015-权限管理-字母形式设置权限-.mp4 [16.9 MB]
📁 02_Linux基本命令1
007-命令入门-.mp4 [36.0 MB]
009-基本命令2-压缩解压缩-.mp4 [66.0 MB]
008-基本命令1-.mp4 [41.3 MB]
📁 17iptables快速入门之五表五链
017_iptables快速入门之五表五链(表实践-信息查看+规则实践)-.mp4 [27.4 MB]
014_iptables快速入门之五表五链(链基础-简介+详解+关系)-.mp4 [28.1 MB]
015_iptables快速入门之五表五链(链实践-顺序+增删改)-.mp4 [34.4 MB]
016_iptables快速入门之五表五链(表简介-简介+详解)-.mp4 [37.5 MB]
019_iptables快速入门之五表五链(小结)-.mp4 [27.9 MB]
018_iptables快速入门之五表五链(表链关系-关系+优先级+编写+场景)-.mp4 [56.4 MB]
📁 04_vim编辑器
008-vim编辑器-案例-.mp4 [6.5 MB]
004-vim编辑器-命令行模式操作-.mp4 [23.3 MB]
007-vim编辑器-实用功能-.mp4 [29.1 MB]
003-vim编辑器介绍及打开文件-.mp4 [21.1 MB]
006-vim编辑器-编辑模式和小结-.mp4 [10.5 MB]
📁 29keepalived 配置详解1
020_快速入门之配置详解(状态检测2)-.mp4 [42.0 MB]
018_快速入门之配置详解(VRRP配置段)-.mp4 [49.5 MB]
019_快速入门之配置详解(状态检测1)-.mp4 [34.3 MB]
021_快速入门之配置详解(状态检测3)-.mp4 [22.1 MB]
017_快速入门之配置详解(全局配置段)-.mp4 [40.4 MB]
📁 21LVS集群基础
002_集群基础之集群简介(集群类型-实现方式)-.mp4 [28.1 MB]
003_集群基础之集群简介(小结)-.mp4 [6.2 MB]
001_集群基础之集群简介(集群基础-场景需求+解决方案+访问流程)-.mp4 [25.0 MB]
000_课程概况-.mp4 [7.2 MB]
📁 03_Linux基本命令2
013-基本命令6-文件内容-.mp4 [42.7 MB]
014-基本命令-日期时间-.mp4 [2.0 GB]
010-基本命令3-.mp4 [20.1 MB]
011-基本命令4-帮助命令-.mp4 [19.8 MB]
015-基本命令-管道命令-.mp4 [982.9 MB]
001-基本命令-其他命令-.mp4 [735.1 MB]
012-基本命令5-磁盘内存命令-.mp4 [10.8 MB]
002-远程连接工具-.mp4 [18.2 MB]
📁 35文件模块、应用模块和命令
034_快速入门之常用模块(系列命令2)-.mp4 [35.4 MB]
033_快速入门之常用模块(系列命令1)-.mp4 [44.7 MB]
035_快速入门之常用模块(系列命令3)-.mp4 [16.5 MB]
029_快速入门之常用模块(文件模块2)-.mp4 [24.5 MB]
028_快速入门之常用模块(文件模块1)-.mp4 [35.4 MB]
032_快速入门之常用模块(应用模块2)-.mp4 [34.5 MB]
030_快速入门之常用模块(文件模块3)-.mp4 [29.6 MB]
031_快速入门之常用模块(应用模块1)-.mp4 [43.5 MB]
📁 32Ansible安装和简单实用
008_快速入门之软件部署(部署简介+准备工作1)-.mp4 [31.4 MB]
007_快速入门之基础知识(简介+功能简介)-.mp4 [29.8 MB]
012_快速入门之软件部署(简单使用2)-.mp4 [32.6 MB]
010_快速入门之软件部署(软件安装)-.mp4 [15.6 MB]
009_快速入门之软件部署(部署简介+准备工作2)-.mp4 [17.8 MB]
011_快速入门之软件部署(简单使用1)-.mp4 [41.8 MB]
📁 07_ssh、日志管理和网络管理
007-ssh-远程传输命令-.mp4 [34.1 MB]
008-日志管理-.mp4 [50.9 MB]
006-ssh-修改sshd端口号-.mp4 [10.2 MB]
009-网络管理-.mp4 [56.8 MB]
010-系统基本优化-.mp4 [26.7 MB]
005-ssh-基于秘钥安全验证-.mp4 [20.3 MB]
004-ssh-基于口令验证-.mp4 [19.7 MB]
📁 24LVS调度策略和DR实践
034_lvs快速入门之DR实践(原理详解)-.mp4 [16.0 MB]
033_lvs快速入门之DR实践(简单实践-案例实践3)-.mp4 [13.8 MB]
030_lvs快速入门之DR实践(简单实践-案例需求+需求分析+技术点分析)-.mp4 [20.2 MB]
026_lvs快速入门之调度策略(wrr实践)-.mp4 [18.3 MB]
025_lvs快速入门之调度策略(调度基础+静态方法+动态方法)-.mp4 [35.0 MB]
027_lvs快速入门之调度策略(sh实践)-.mp4 [12.8 MB]
035_lvs快速入门之DR实践(应用技巧)-.mp4 [24.3 MB]
032_lvs快速入门之DR实践(简单实践-案例实践2)-.mp4 [25.8 MB]
031_lvs快速入门之DR实践(简单实践-案例实践1)-.mp4 [34.1 MB]
028_lvs快速入门之DR实践(前置知识-ARP表+交换机原理+地址冲突)-.mp4 [38.4 MB]
029_lvs快速入门之DR实践(DR模型-模型简介+模型分析)-.mp4 [20.0 MB]
📁 44nagios配置详解1
021_快速入门之配置详解(原理详解)-.mp4 [29.8 MB]
015_快速入门之配置详解(目录结构+配置详解)-.mp4 [46.4 MB]
019_快速入门之配置详解(mysql实践1)-.mp4 [48.2 MB]
020_快速入门之配置详解(mysql实践2)-.mp4 [20.1 MB]
018_快速入门之配置详解(简单实践2)-.mp4 [25.5 MB]
014_快速入门之配置详解(目录结构)-.mp4 [37.3 MB]
017_快速入门之配置详解(简单实践1)-.mp4 [47.1 MB]
016_快速入门之配置详解(核心资源)-.mp4 [39.4 MB]
📁 34日常模块和系统模块
027_快速入门之常用模块(系统模块4)-.mp4 [23.1 MB]
022_快速入门之常用模块(日常模块1)-.mp4 [41.9 MB]
026_快速入门之常用模块(系统模块3)-.mp4 [33.2 MB]
025_快速入门之常用模块(系统模块2)-.mp4 [29.9 MB]
023_快速入门之常用模块(日常模块2)-.mp4 [33.7 MB]
024_快速入门之常用模块(系统模块1)-.mp4 [46.7 MB]
📁 40ansible进阶之模板
055_ansible进阶之模板(快速入门)-.mp4 [45.0 MB]
054_ansible进阶之模板(模板基础)-.mp4 [24.4 MB]
058_第三天总结-.mp4 [22.9 MB]
062_ansible进阶之模板(流程基础1)-.mp4 [17.4 MB]
064_ansible进阶之模板(for流程1)-.mp4 [19.1 MB]
063_ansible进阶之模板(if流程)-.mp4 [40.7 MB]
061_ansible进阶之模板(迭代进阶2)-.mp4 [37.9 MB]
060_ansible进阶之模板(迭代进阶1)-.mp4 [21.8 MB]
057_ansible进阶之模板(条件2)-.mp4 [27.5 MB]
056_ansible进阶之模板(条件1)-.mp4 [44.3 MB]
065_ansible进阶之模板(for流程2)-.mp4 [34.0 MB]
059_ansible进阶之模板(迭代)-.mp4 [30.2 MB]
📁 38ansible进阶之变量
053_ansible进阶之变量进阶(变量-专用文件)-.mp4 [31.0 MB]
048_ansible进阶之变量进阶(变量基础)-.mp4 [24.0 MB]
052_ansible进阶之变量进阶(变量-playbook)-.mp4 [21.1 MB]
049_ansible进阶之变量进阶(变量-主机属性)-.mp4 [29.7 MB]
050_ansible进阶之变量进阶(变量-主机列表)-.mp4 [41.3 MB]
051_ansible进阶之变量进阶(变量-命令行)-.mp4 [27.7 MB]
📁 20iptables快速入门之地址转换
035_iptables快速入门之规则进阶(地址转换-SNAT进阶实践)-.mp4 [18.1 MB]
036_iptables快速入门之规则进阶(地址转换-DNAT实践)-.mp4 [24.3 MB]
034_iptables快速入门之规则进阶(地址转换-SNAT实践)-.mp4 [29.6 MB]
037_iptables快速入门之规则进阶(小结)-.mp4 [30.8 MB]
033_iptables快速入门之规则进阶(地址转换-案例需求+准备环境)-.mp4 [39.4 MB]
📁 33Ansible部署
016_快速入门之软件部署(配置详解)-.mp4 [45.6 MB]
018_快速入门之软件部署(简单实践2)-.mp4 [33.2 MB]
013_快速入门之软件部署(主机清单1)-.mp4 [42.5 MB]
020_快速入门之软件部署(主机进阶实践)-.mp4 [48.3 MB]
015_快速入门之软件部署(原理详解)-.mp4 [29.7 MB]
014_快速入门之软件部署(主机清单2)-.mp4 [29.5 MB]
021_快速入门之软件部署(命令执行过程)-.mp4 [30.7 MB]
019_第一天总结-.mp4 [31.7 MB]
017_快速入门之软件部署(简单实践1)-.mp4 [32.5 MB]
📁 11_shell基础之变量
005_shell基础之变量(变量基础-定位+分类)-.mp4 [14.0 MB]
008_shell基础之变量(查看&取消-查看+取消)-.mp4 [11.3 MB]
010_shell基础之变量(内置变量-精确截取+默认值)-.mp4 [26.5 MB]
009_shell基础之变量(内置变量-定义+脚本文件)-.mp4 [33.8 MB]
010_shell基础之小结-.mp4 [19.8 MB]
006_shell基础之变量(本地变量-定义+普通变量+命令变量)-.mp4 [29.5 MB]
007_shell基础之变量(全局变量-定义+查看+定义)-.mp4 [14.2 MB]
📁 09_apache虚拟主机、防盗链和日志切割
015-防盗链-.mp4 [27.9 MB]
011-基于ip的虚拟主机-.mp4 [23.4 MB]
016-域名跳转-.mp4 [24.6 MB]
017-日志切割-rotatelogs-.mp4 [14.3 MB]
012-基于域名的虚拟主机-.mp4 [17.1 MB]
018-日志切割-cronolog-.mp4 [18.2 MB]
014-rewrite-.mp4 [24.4 MB]
013-基于端口的虚拟主机-.mp4 [21.0 MB]
📁 19iptables快速入门之web扩展和网络防火墙
031_iptables快速入门之规则进阶(网络防火墙-需求场景+基本环境)-.pcwlenv [31.7 MB]
027_iptables快速入门之规则进阶(web扩展-时间扩展实践)-.pcwlenv [33.0 MB]
032_iptables快速入门之规则进阶(网络防火墙-web服务+防火墙实践)-.pcwlenv [37.2 MB]
029_iptables快速入门之规则进阶(web扩展-ip并发+内容并发实践)-.pcwlenv [56.2 MB]
030_iptables快速入门之规则进阶(web扩展-连接状态实践)-.pcwlenv [31.5 MB]
028_iptables快速入门之规则进阶(web扩展-内容扩展实践)-.pcwlenv [24.4 MB]
📁 36playbook基础
038_第二天总结-.mp4 [28.6 MB]
036_快速入门之playbook(基础)-.mp4 [23.6 MB]
037_快速入门之playbook(YAML详解)-.mp4 [50.8 MB]
039_快速入门之playbook(基础属性1)-.mp4 [55.3 MB]
041_快速入门之playbook(基础属性3)-.mp4 [35.5 MB]
042_快速入门之playbook(基础属性4)-.mp4 [23.1 MB]
040_快速入门之playbook(基础属性2)-.mp4 [23.5 MB]
📁 28keepalived 软件部署
013_快速入门之软件部署(负载均衡1)-.mp4 [50.0 MB]
016_快速入门之小结-.mp4 [35.2 MB]
012_快速入门之软件部署(故障演练)-.mp4 [30.0 MB]
010_快速入门之软件部署(配置实践)-.mp4 [40.7 MB]
014_快速入门之软件部署(负载均衡2)-.mp4 [43.8 MB]
015_快速入门之软件部署(负载均衡3)-.mp4 [17.7 MB]
011_快速入门之软件部署(配置实践2)-.mp4 [10.9 MB]
009_快速入门之软件部署(配置简介)-.mp4 [38.0 MB]
008_快速入门之软件部署(安装软件)-.mp4 [46.5 MB]
📁 42监控知识体系
003_监控知识体系之监控工具(系统命令+开源软件+第三方平台)-.mp4 [36.0 MB]
002_监控知识体系之监控概述(监控原理)-.mp4 [26.3 MB]
000_课程概况-.mp4 [6.5 MB]
001_监控知识体系之监控概述(为什么要监控)-.mp4 [33.0 MB]
📁 15安全知识体系
006_安全知识体系之防火墙基础(功能-分层管控+数据包过滤)-.mp4 [35.1 MB]
004_安全知识体系之防火墙基础(简介-场景需求+简介)-.mp4 [22.8 MB]
000_课程概况-.mp4 [7.2 MB]
001_安全知识体系之安全概述(安全现状-安全场景+安全案例+项目现状)-.mp4 [17.8 MB]
003_安全知识体系之安全概述(安全措施-角色定位+安全措施)-.mp4 [12.8 MB]
002_安全知识体系之安全概述(安全体系-硬件+基础+应用+业务+运营)-.mp4 [21.1 MB]
007_安全知识体系之小结-.mp4 [13.1 MB]
📁 46远程监控
035_快速入门之远程监控(nrpe实践2)-.pcwlenv [23.2 MB]
029_快速入门之远程监控(被动流程)-.pcwlenv [17.5 MB]
034_快速入门之远程监控(nrpe实践1)-.pcwlenv [37.3 MB]
032_快速入门之远程监控(远程主机部署2)-.pcwlenv [45.3 MB]
031_快速入门之远程监控(远程主机部署1)-.pcwlenv [38.5 MB]
039_第二天总结-.pcwlenv [25.6 MB]
038_第一天总结-.pcwlenv [31.1 MB]
037_快速入门之远程监控(脚本开发2)-.pcwlenv [37.6 MB]
030_快速入门之远程监控(准备工作)-.pcwlenv [38.3 MB]
033_快速入门之远程监控(命令详解)-.pcwlenv [45.4 MB]
036_快速入门之远程监控(脚本开发1)-.pcwlenv [38.6 MB]
📁 13_shell核心知识常见符号和流程控制
018_核心知识之常见符号(其他符号)-.mp4 [28.3 MB]
021_核心知识之简单流程控制(case语句-格式+实践)-.mp4 [27.6 MB]
022_核心知识之简单流程控制(循环语句-for+while+until)-.mp4 [29.9 MB]
020_核心知识之简单流程控制(if语句-多分支+实践)-.mp4 [27.5 MB]
019_核心知识之简单流程控制(if语句-单分支+双分支)-.mp4 [19.5 MB]
023_核心知识之简单流程控制(循环退出-简介+break+break n)-.mp4 [30.4 MB]
024_核心知识之简单流程控制(循环退出-continue+exit)-.mp4 [20.1 MB]
026_核心知识之复杂流程控制(函数-脚本传参+生产用法)-.mp4 [22.3 MB]
025_核心知识之复杂流程控制(函数-简介+简单+传参)-.mp4 [26.7 MB]
017_核心知识之常见符号(重定向+管道符)-.mp4 [14.5 MB]
📁 39keepalived 原理详解和综合实践
031_快速入门之综合实践(双主方式1)-.mp4 [16.7 MB]
032_快速入门之综合实践(双主方式2)-.mp4 [38.2 MB]
029_快速入门之原理详解(结构详解)-.mp4 [46.0 MB]
033_快速入门之综合实践(双主方式3)-.mp4 [31.6 MB]
030_快速入门之原理详解(路由详解)-.mp4 [44.0 MB]
034_快速入门之综合实践(小结)-.mp4 [14.4 MB]
📁 01_Linux系统安装和认识
001-linux概述-.mp4 [18.0 MB]
005-备份操作系统-.mp4 [23.7 MB]
003-linux安装一-.mp4 [34.0 MB]
002-虚拟机创建-.mp4 [41.5 MB]
006-系统认识-.mp4 [12.9 MB]
004-linux安装二-.mp4 [7.9 MB]
📁 06_软件管理和计划任务
002-计划任务-at-.mp4 [27.3 MB]
003-计划任务-cron-.mp4 [47.9 MB]
019-软件管理-源码包-.mp4 [41.1 MB]
020-软件管理-rpm和yum-.mp4 [532.0 KB]
001-运行模式-.mp4 [27.9 MB]
📁 14_shell核心知识之常见命令
030_核心知识之常见命令(awk1)-.mp4 [25.0 MB]
034_核心知识之常见命令(find1)-.mp4 [44.9 MB]
029_核心知识之常见命令(sed2)-.mp4 [24.9 MB]
027_核心知识之常见命令(grep)-.mp4 [31.6 MB]
032_核心知识之常见命令(awk3)-.mp4 [19.9 MB]
031_核心知识之常见命令(awk2)-.mp4 [29.6 MB]
033_核心知识之常见命令(awk4)-.mp4 [31.2 MB]
036_核心知识之小结-.mp4 [23.1 MB]
035_核心知识之常见命令(find2)-.mp4 [26.6 MB]
📁 23LVS快速入门之NAT实战
014_lvs快速入门之NAT实践(简单实践-案例需求+基础环境设置)-.mp4 [21.5 MB]
023_lvs快速入门之NAT实践(小结)-.mp4 [20.2 MB]
022_lvs快速入门之NAT实践(进阶实践2-集群实践+小结)-.mp4 [12.1 MB]
020_lvs快速入门之NAT实践(进阶实践2-场景需求+需求分析+关键点分析+实践)-.mp4 [23.0 MB]
012_lvs快速入门之NAT实践(NAT简介-模型简介+模型分析)-.mp4 [23.3 MB]
015_lvs快速入门之NAT实践(简单实践-web服务+lvs集群设置)-.mp4 [31.5 MB]
016_lvs快速入门之NAT实践(原理详解-流程详解+数据包详解+请求流程)-.mp4 [27.9 MB]
019_lvs快速入门之NAT实践(进阶实践1-实践小结+数据包分析)-.mp4 [25.2 MB]
018_lvs快速入门之NAT实践(进阶实践-场景需求+需求分析+关键点分析+实践)-.mp4 [34.3 MB]
021_lvs快速入门之NAT实践(进阶实践2-https实践)-.mp4 [27.3 MB]
017_lvs快速入门之NAT实践(应用技巧-原理技巧+应用技巧)-.mp4 [30.0 MB]
013_lvs快速入门之NAT实践(简单实践-案例需求+需求分析+关键点分析)-.mp4 [24.3 MB]
011_lvs快速入门之NAT实践(前置知识-网络设备+基本环境)-.mp4 [25.6 MB]
📁 资料
05阶段：项目测试和监控.exe [233.8 MB]
01_基础班.exe [366.6 MB]
11阶段：爬虫进价方向【选修】.exe [194.0 MB]
09阶段：黑马文学.exe [69.4 MB]
04阶段：项目部署和管理.exe [1.2 GB]
07阶段：Web-Flask框架与项目.exe [4.1 GB]
python安装包.exe [5.2 GB]
12阶段：WEB方向进价【选修】.exe [66.2 MB]
13阶段：运维开发方向【选修】.exe [268.0 MB]
02阶段：python高级.exe [103.6 MB]
06阶段：数据采集.exe [43.7 MB]
应用安装包.exe [1.4 GB]
08阶段：数据分析课程.exe [7.3 GB]
03阶段：Django框架与项目.exe [148.8 MB]
14阶段：深度学习进价方向【选修】.exe [2.9 GB]
10阶段：云课堂.exe [1.5 GB]
📁 02阶段_python高级
📁 Day16
📁 Day02
📁 Day06
📁 Day09
📁 Day14
📁 Day12
📁 Day01
📁 Day11
📁 Day07
📁 Day08
📁 Day03
📁 Day15
📁 Day13
📁 Day05
📁 Day10
📁 Day04
📁 10-云课堂
📁 13_订单与选课
7.3.1QQ自动添加选课方案-环境搭建_.mp4 [28.5 MB]
7.2.4QQ分布式事务解决方案_.mp4 [44.8 MB]
7.1QQ订单与选课需求分析_.mp4 [26.4 MB]
7.6.1QQ自动添加选课-RabbitMQ配置_.mp4 [22.0 MB]
7.2.3QQCAP理论_.mp4 [33.0 MB]
7.5.1QQ订单服务定时发送消息-需求分析_.mp4 [7.2 MB]
7.6.2QQ自动添加选课-学习服务添加选课_.mp4 [36.5 MB]
7.2.1QQ问题描述_.mp4 [19.3 MB]
7.3.2QQ自动添加选课方案-解决方案_.mp4 [16.5 MB]
7.2.2QQ什么是分布式事务_.mp4 [25.8 MB]
7.4QQCeleryQQBeat定时任务_.mp4 [51.1 MB]
7.6.4QQ自动添加选课-集成测试_.mp4 [13.8 MB]
7.6.3QQ自动添加选课-订单服务结束任务_.mp4 [19.9 MB]
7.5.2QQ订单服务定时发送消息-查询前N条任务_.mp4 [37.5 MB]
📁 6_课程管理-我的课程基本信息及营销信息
3.3.3QQ数据字典_.mp4 [60.0 MB]
3.3.6QQ新增课程前端_.mp4 [29.4 MB]
3.3.5QQ创建课程服务端_.mp4 [8.7 MB]
3.4.1QQ课程信息修改需求分析_.mp4 [7.2 MB]
3.2.2QQ我的课程后端_.mp4 [23.4 MB]
3.3.2QQ课程分类查询_.mp4 [77.4 MB]
3.2.3QQ我的课程前端2-api及测试_.mp4 [27.5 MB]
3.1.1QQ需求分析_.mp4 [22.3 MB]
3.5.2QQ课程营销数据模型_.mp4 [4.3 MB]
3.1.2QQ环境搭建_.mp4 [36.4 MB]
3.5.3QQ课程营销信息服务端_.mp4 [39.7 MB]
3.3.4QQ新增课程页面内容完善_.mp4 [56.5 MB]
3.4.3QQ课程修改服务端_.mp4 [14.0 MB]
3.4.2QQ课程管理页面说明_.mp4 [70.8 MB]
3.4.4QQ课程修改前端_.mp4 [51.8 MB]
3.2.3QQ我的课程前端1-页面布局_.mp4 [33.3 MB]
3.5.4QQ课程营销前端_.mp4 [39.4 MB]
3.5.1QQ课程营销需求分析_.mp4 [9.7 MB]
3.3.1QQ创建课程需求分析_.mp4 [6.2 MB]
3.2.1QQ我的课程需求分析_.mp4 [9.8 MB]
📁 7_课程管理-课程计划及课程图片
3.6.3.3QQ添加课程计划服务端_.mp4 [25.9 MB]
3.7.1.2QQ文件系统服务环境搭建_.mp4 [19.8 MB]
3.7.2.1QQ保存课程图片需求分析_.mp4 [7.9 MB]
3.7.4.1QQ图片删除需求分析_.mp4 [8.8 MB]
3.7.4.3QQ图片删除前端_.mp4 [38.9 MB]
3.6.2.1QQ课程计划查询功能分析_.mp4 [7.5 MB]
3.7.3.3QQ图片查询前端_.mp4 [25.6 MB]
3.7.4.2QQ图片删除服务端_.mp4 [19.4 MB]
3.7.1.3QQ上传图片服务端_.mp4 [74.4 MB]
3.6.2.3QQ课程计划服务端_.mp4 [59.8 MB]
3.6.1QQ课程计划需求分析_.mp4 [12.1 MB]
3.7.1.4QQ上传图片前端_.mp4 [39.5 MB]
3.6.2.4QQ课程计划前端页面_.mp4 [43.9 MB]
3.7.3.1-2QQ图片查询需求分析与服务端_.mp4 [12.3 MB]
3.7.1.1QQ上传图片需求分析_.mp4 [19.1 MB]
3.7.2.3QQ保存图片前端_.mp4 [32.3 MB]
3.6.3.2QQ添加课程计划页面原型_.mp4 [35.7 MB]
3.6.2.2QQ课程计划页面原型_.mp4 [35.9 MB]
3.6.3.1QQ添加课程计划需求分析_.mp4 [9.2 MB]
3.6.3.4QQ添加课程计划前端_.mp4 [25.5 MB]
3.7.2.2QQ保存图片服务端_.mp4 [34.3 MB]
📁 11_学习中心与媒资管理
5.11.3QQ在线学习后端开发_.mp4 [28.6 MB]
5.8.3QQ保存视频信息2-前端开发与测试_.mp4 [35.0 MB]
5.1.2QQ视频点播解决方案_.mp4 [52.8 MB]
5.1.1QQ在线学习需求描述_.mp4 [13.1 MB]
5.10.4QQ搜索服务查询媒资接口_.mp4 [31.7 MB]
5.9.4QQ学习页面查询课程计划前端开发_.mp4 [40.4 MB]
5.11.4QQ在线学习前端开发_.mp4 [65.9 MB]
5.7.3QQ我的媒资前端开发_.mp4 [31.4 MB]
5.6.2QQ视频处理开发4-Mp4VideoUtil_.mp4 [33.2 MB]
5.8.3QQ保存视频信息1-需求分析后端实现_.mp4 [56.3 MB]
5.6.2QQ视频处理开发7-视频处理_.mp4 [88.0 MB]
5.5.2QQ开发环境_.mp4 [11.6 MB]
5.7.2QQ我的媒资服务端开发_.mp4 [34.7 MB]
5.11.1QQ在线学习需求分析_.mp4 [5.1 MB]
5.8.1QQ媒资与课程计划关联需求分析_.mp4 [11.1 MB]
5.6.2QQ视频处理开发2-视频处理技术方案_.mp4 [21.3 MB]
5.10.2QQ课程发布存储媒资信息1-需求分析_.mp4 [7.5 MB]
5.5.1QQ媒资管理需求分析_.mp4 [19.2 MB]
5.5.3.1QQ断点续传解决方案_.mp4 [17.3 MB]
5.10.3QQlogstash扫描课程计划媒资_.mp4 [28.2 MB]
5.7.1QQ我的媒资需求分析_.mp4 [9.4 MB]
5.3QQ播放器_.mp4 [40.1 MB]
5.10.2QQ课程发布存储媒资信息2-后端实现_.mp4 [50.0 MB]
5.5.3.2QQ文件分块与合并2-文件分块_.mp4 [25.9 MB]
5.2.3QQ生成m3u8_ts文件_.mp4 [43.6 MB]
5.5.3.2QQ文件分块与合并1-获取文件md5_.mp4 [21.8 MB]
5.6.2QQ视频处理开发5-HlsVideoUtil_.mp4 [62.1 MB]
5.6.2QQ视频处理开发3-VideoUtil_.mp4 [57.9 MB]
5.10.1QQ学习页面获取播放地址需求分析_.mp4 [18.2 MB]
5.6.1QQ视频处理需求分析_.mp4 [11.3 MB]
5.8.4QQ查询视频信息_.mp4 [40.4 MB]
5.9.3QQ学习页面查询课程计划服务端开发_.mp4 [16.9 MB]
5.11.2QQ搭建开发环境_.mp4 [11.5 MB]
5.8.2QQ选择视频1-父子组件通信_.mp4 [15.1 MB]
5.6.2QQ视频处理开发6-处理流程准备_.mp4 [11.4 MB]
5.9.1-2QQ学习页面查询课程计划需求与api接口_.mp4 [9.6 MB]
5.6.3QQ发送视频处理消息_.mp4 [17.1 MB]
5.8.2QQ选择视频2-前端实现_.mp4 [56.4 MB]
5.2.1QQ视频编码格式_.mp4 [13.7 MB]
5.6.2QQ视频处理开发1-基础配置_.mp4 [20.7 MB]
5.4QQ搭建学习中心前端_.mp4 [32.3 MB]
📁 2_cms-环境搭建
2.3.5QQ删除数据_.mp4 [9.8 MB]
2.3.4QQ修改数据_.mp4 [10.2 MB]
2.3.7QQQ对象_.mp4 [13.7 MB]
2.3.1QQ在django中使用MongoDB_.mp4 [22.3 MB]
2.2.1QQ静态门户工程搭建_.mp4 [27.6 MB]
2.2.3QQcms页面管理需求_.mp4 [16.2 MB]
2.3.3QQ增加数据_.mp4 [10.9 MB]
2.3.2QQ定义文档_.mp4 [44.4 MB]
2.3.6QQ查询数据_.mp4 [29.0 MB]
2.3.8QQ其他_.mp4 [25.4 MB]
2.3.9QQ查询集_.mp4 [16.8 MB]
2.2.2QQssi服务端包含技术_.mp4 [56.8 MB]
📁 4_cms-页面管理前端
2.5.2.4QQ分页查询测试_.mp4 [18.1 MB]
2.5.2.3QQ跨域问题解决_.mp4 [40.0 MB]
2.5.1.2QQ单页面应用介绍_.mp4 [20.4 MB]
2.5.2.2QQapi调用_.mp4 [36.7 MB]
2.5.2.6QQ自定义条件查询_.mp4 [52.9 MB]
2.5.1.1QQ导入系统管理前端工程_.mp4 [27.6 MB]
2.5.2.1.1QQ创建页面_.mp4 [32.5 MB]
2.5.3.1QQ新增页面2-页面完善_.mp4 [49.7 MB]
2.5.4.1-2QQ页面处理流程QQ修改页面_.mp4 [44.6 MB]
2.5.2.1.3QQ页面内容完善_.mp4 [41.7 MB]
2.5.2.7QQ前后端请求响应小结_.mp4 [16.7 MB]
2.5.3.1QQ新增页面1_.mp4 [46.0 MB]
2.5.2.5QQ进入页面立即查询_.mp4 [15.7 MB]
2.5.4.3QQapi调用_.mp4 [22.2 MB]
2.5.5QQ删除页面前端开发_.mp4 [23.9 MB]
2.5.2.1.2QQTable组件测试_.mp4 [30.9 MB]
2.5.3.2-3QQapi调用-添加页面测试_.mp4 [24.1 MB]
📁 12_登录注册与认证授权
6.5QQ用户退出_.mp4 [22.5 MB]
6.7QQ用户注册后端1-发送验证码_.mp4 [86.1 MB]
6.6QQ前端集成认证授权_.mp4 [49.4 MB]
6.1QQJWT_.mp4 [55.4 MB]
6.3QQ用户登录前端_.mp4 [67.1 MB]
6.4QQ前端显示当前用户_.mp4 [35.8 MB]
6.7QQ用户注册后端1-用户注册_.mp4 [61.4 MB]
6.8QQ用户注册前端_.mp4 [31.9 MB]
6.2QQDjangorestfremework-jwt_.mp4 [42.9 MB]
📁 9_课程搜索-搜索后端
4.2.4QQLogstash创建索引_.pcwlenv [116.0 MB]
4.3.1QQ课程搜索功能需求_.pcwlenv [12.7 MB]
4.2.1QQ课程索引技术方案_.pcwlenv [13.4 MB]
4.3.3QQ定义ESClient2-BaseESClient实现_.pcwlenv [66.9 MB]
4.3.2QQ创建搜索应用_.pcwlenv [20.0 MB]
4.3.4QQ课程搜索服务端开发_.pcwlenv [29.2 MB]
4.3.3QQ定义ESClient3-ESClient实现及测试_.pcwlenv [66.0 MB]
4.1QQ课程搜索需求分析_.pcwlenv [20.0 MB]
4.2.2QQ准备课程索引信息_.pcwlenv [131.7 MB]
4.3.3QQ定义ESClient1-代码讲解_.pcwlenv [50.3 MB]
4.2.3QQ搭建ES环境_.pcwlenv [29.9 MB]
📁 3_cms-页面管理后端
2.4.5QQ新增页面_.mp4 [61.9 MB]
2.4.8QQ修改页面_.mp4 [20.4 MB]
2.4.6.3QQ自定义条件查询_.mp4 [32.5 MB]
2.4.6.1QQ需求分析_.mp4 [6.3 MB]
2.4.6.2QQ分页查询_.mp4 [56.9 MB]
2.4.9QQ删除页面_.mp4 [21.7 MB]
2.4.4QQ站点列表和模板列表_.mp4 [41.7 MB]
2.4.2.2QQ封装异常处理_.mp4 [74.1 MB]
2.4.3QQ数据模型定义_.mp4 [22.7 MB]
2.4.7QQ页面详情_.mp4 [18.8 MB]
2.4.1QQ使用MongoEngine定义接口_.mp4 [40.6 MB]
2.4.2.1QQ接口开发规范_.mp4 [16.2 MB]
2.4.2.3QQ封装JSON返回值_.mp4 [40.1 MB]
📁 8_课程管理-课程预览与发布
3.9.4QQ课程发布前端开发_.mp4 [25.8 MB]
3.8.2.1QQ静态页面测试_.mp4 [42.9 MB]
3.8.3.3QQCMS添加页面接口_.mp4 [29.9 MB]
3.8.3.4QQ课程预览服务端_.mp4 [69.5 MB]
3.8.3.5QQ课程预览前端_.mp4 [28.0 MB]
3.9.3QQ课程发布接口_.mp4 [32.4 MB]
3.8.1QQ课程预览技术方案_.mp4 [39.3 MB]
3.8.2.2QQ课程数据模型查询接口_.mp4 [40.7 MB]
3.9.1QQ课程发布需求分析_.mp4 [13.2 MB]
3.9.2QQCMS一键发布接口_.mp4 [38.4 MB]
3.8.2.3QQ课程信息模板设计_.mp4 [31.7 MB]
3.8.3.2QQCMS页面预览测试_.mp4 [18.9 MB]
📁 5_cms-课程静态化及预览发布
2.6.3.1QQ页面预览开发_.mp4 [30.5 MB]
2.6.4.3QQ页面发布消费方_.mp4 [61.4 MB]
2.6.4.6QQ测试_.mp4 [21.1 MB]
2.6.4.2QQ技术方案_.mp4 [12.1 MB]
2.6.2.2QQ数据模型_.mp4 [58.3 MB]
2.6.4.1QQ需求分析_.mp4 [16.2 MB]
2.6.1QQ页面静态化需求_.mp4 [12.2 MB]
2.6.4.4QQ页面发布生产方_.mp4 [49.6 MB]
2.6.2.3.1QQ模板管理业务流程_.mp4 [9.1 MB]
2.6.2.1QQ页面静态化流程_.mp4 [20.7 MB]
2.6.2.3.3QQGridFS研究_.mp4 [56.7 MB]
2.6.2.3.5-1QQ静态化程序_.mp4 [67.7 MB]
2.6.2.3.4QQ模板存储_.mp4 [28.6 MB]
2.6.2.3.2QQ模板制作_.mp4 [52.5 MB]
2.6.2.3.5-2QQ静态化程序测试_.mp4 [23.6 MB]
2.6.4.5QQ页面发布前端实现_.mp4 [24.3 MB]
2.6.3.2QQ页面预览测试_.mp4 [28.7 MB]
📁 10_课程搜索-搜索前端
4.7QQ集成测试_.mp4 [11.5 MB]
4.4.2QQ服务端渲染和客户端渲染_.mp4 [28.9 MB]
4.4.1QQ了解SEO_.mp4 [23.1 MB]
4.6.4QQ按分类搜索_.mp4 [56.1 MB]
4.6.1QQ搜索页面_.mp4 [43.4 MB]
4.6.5QQ按难度等级搜索_.mp4 [12.5 MB]
4.5.2QQ创建nuxt工程_.mp4 [20.7 MB]
4.5.1QQnuxt.js介绍_.mp4 [27.1 MB]
4.6.2QQ查询全部_.mp4 [43.4 MB]
4.5.4QQ路由_.mp4 [32.4 MB]
4.5.5QQ获取数据_.mp4 [48.1 MB]
4.6.3QQ分页查询_.mp4 [22.2 MB]
4.5.3QQ页面布局_.mp4 [12.7 MB]
📁 1_项目概述
1.1QQ传智云课堂项目背景_.mp4 [11.8 MB]
1.3QQ项目的技术架构_.mp4 [24.5 MB]
1.2QQ项目的功能架构_.mp4 [25.8 MB]
📁 06_数据采集
📁 04_selenium
02.selenium的工作原理_.mp4 [21.9 MB]
03.selenium-模块与driver的安装_.mp4 [98.8 MB]
11.selenium-执行js_.mp4 [119.8 MB]
12.selenium-页面等待_.mp4 [77.7 MB]
05.selenium-driver属性和方法_.mp4 [27.5 MB]
04.selenium-简单使用_.mp4 [36.2 MB]
09.selenium-窗口切换_.mp4 [125.8 MB]
08.selenium-标签切换_.mp4 [111.8 MB]
06.selenium-元素定位_.mp4 [184.1 MB]
10.selenium-cookies操作_.mp4 [64.4 MB]
13.selenium-配置对象_.mp4 [27.1 MB]
01.selenium-介绍_效果展示_.mp4 [87.9 MB]
14.selenium-案例-斗鱼直播_.mp4 [568.1 MB]
07.selenium-元素操作_.mp4 [54.5 MB]
📁 07_scrapy基础
13.请求对象-meta传参_.mp4 [29.6 MB]
05.项目开发流程-2创建项目_.mp4 [8.9 MB]
07.项目开发流程-4完成爬虫_.mp4 [61.9 MB]
18.tencent_crawl_.mp4 [55.1 MB]
15.scrapy模拟登陆-FormRequest发送post请求_.mp4 [34.3 MB]
04.项目开发流程-1框架安装&流程简介_.mp4 [3.9 MB]
20.中间件-豆瓣爬虫_.mp4 [169.9 MB]
19.中间件-分类与作用_.mp4 [95.6 MB]
14.scrapy模拟登陆-cookies参数使用_.mp4 [31.4 MB]
03.scrapy-各模块功能_.mp4 [10.9 MB]
21.中间件-随机请求头_.mp4 [115.0 MB]
16.scrapy管道的使用_.mp4 [64.8 MB]
11.请求对象-案例-网易招聘_.mp4 [55.8 MB]
22.中间件-随机ip代理_.mp4 [204.4 MB]
06.项目开发流程-3创建爬虫_.mp4 [25.1 MB]
17.crawlspider_.mp4 [39.1 MB]
23.中间件-selenium动态加载_.mp4 [282.7 MB]
01.scrapy-概念&作用_.mp4 [6.4 MB]
08.项目开发流程-5保存数据_.mp4 [122.6 MB]
12.请求对象-其他参数_.mp4 [14.8 MB]
10.请求对象-请求&网易招聘简介_.mp4 [7.3 MB]
09.项目开发流程-数据建模&流程完善_.mp4 [22.0 MB]
02.scrapy-工作流程_.mp4 [32.3 MB]
📁 10_appium
01.appium简介_.mp4 [48.3 MB]
03.appium环境联调测试_.mp4 [120.9 MB]
02.appium环境搭建_.mp4 [288.2 MB]
04.appium使用_.mp4 [156.9 MB]
📁 08_scrapy-redis
04.scrapy-redis-分布式爬虫实现_.mp4 [285.8 MB]
02.scrapy-redis-断点续爬_.mp4 [243.3 MB]
01.scrapy-redis-分布式的概念_原理_.mp4 [169.7 MB]
08.scrapy-redis-京东爬虫-图书列表页面_.mp4 [197.0 MB]
09.scrapy-redis-京东爬虫-图书价格_.mp4 [216.3 MB]
07.scrapy-redis-京东爬虫-图书分类页面_.mp4 [199.0 MB]
03.scrapy-redis-源码分析_.mp4 [342.3 MB]
10.scrapy-redis-京东爬虫-修改成分布式爬虫_.mp4 [236.1 MB]
06.scrapy-redis-京东爬虫-简介_.mp4 [187.4 MB]
05.scrapy-redis-分布式爬虫编写流程_.mp4 [38.3 MB]
📁 01_爬虫基础
04.爬虫的作用_.mp4 [178.7 MB]
09.创建的响应状态码_.mp4 [75.6 MB]
06.爬虫的流程_.mp4 [46.2 MB]
10.浏览器运行过程_.mp4 [148.4 MB]
02.课程结构_.mp4 [12.7 MB]
05.爬虫的分类_.mp4 [68.2 MB]
03.爬虫的概念_.mp4 [32.7 MB]
01.爬虫特点介绍_.mp4 [35.4 MB]
08.常见的请求头与响应头_.mp4 [164.3 MB]
07.http与https的区别_.mp4 [27.6 MB]
📁 06_MongoDB数据库
15.mongodb的权限管理-管理用户_.mp4 [10.3 MB]
06.mongdb简单使用-集合操作_.mp4 [19.7 MB]
03.mongodb简单使用-测试启动_.mp4 [47.1 MB]
04.mongodb简单使用-生产启动_.mp4 [91.6 MB]
14.mongodb-索引_.mp4 [34.7 MB]
11.mongodb-修改&删除_.mp4 [29.7 MB]
02.mongodb的安装_.mp4 [38.2 MB]
05.mongodb简单使用-数据库操作_.mp4 [7.9 MB]
01.mongodb的介绍_.mp4 [43.0 MB]
13.聚合管道-其他管道_.mp4 [30.1 MB]
08.mongdb插入数据_.mp4 [16.3 MB]
12.聚合管道-分组管道_.mp4 [29.7 MB]
09.mongodb查询数据_.mp4 [26.3 MB]
10.mongodb查询结果操作_.mp4 [19.8 MB]
17.pymongo使用_.mp4 [34.8 MB]
16.mongodb权限管理-普通用户_.mp4 [13.7 MB]
07.mongodb的数据类型_.mp4 [12.7 MB]
📁 09_scrapy其他
03.scrapy-日志信息_.mp4 [142.7 MB]
02.splash-使用_.mp4 [118.5 MB]
07.使用Gerapy进行爬虫管理_.mp4 [104.0 MB]
04.scrpay配置-常用配置_.mp4 [127.2 MB]
01.splash-介绍_环境配置_.mp4 [111.8 MB]
06.使用scrapyd进行爬虫部署_.mp4 [130.0 MB]
05.scrapy配置-其他配置_.mp4 [69.8 MB]
📁 03_数据提取
07.lxml简介_.mp4 [29.7 MB]
09.xpath语法-基础节点选择_.mp4 [149.4 MB]
03.常用数据解析方法_.mp4 [18.3 MB]
01.数据提取-响应内容的分类_.mp4 [168.4 MB]
13.百度贴吧_.mp4 [90.7 MB]
04.jsonpath-场景-安装-使用_.mp4 [54.8 MB]
06.jsonpath-案例-拉钩_.mp4 [36.0 MB]
02.xml与html_.mp4 [22.7 MB]
11.xpath语法-其他常用语法_.mp4 [16.5 MB]
08.xpathhelper简介_安装_.mp4 [64.4 MB]
14.tostring_.mp4 [17.2 MB]
12.lxml使用_.mp4 [137.2 MB]
10.xpath语法-节点修饰语法_.mp4 [458.1 MB]
05.jsonpath-练习_.mp4 [29.6 MB]
📁 02_requests模块
7.requests模块-cookies参数的使用_.mp4 [89.6 MB]
12.requests模块-post请求_金山翻译案例_.mp4 [170.9 MB]
8.requests模块-cookiejar对象的处理_.mp4 [26.2 MB]
6.requests模块-在headers中设置cookies参数_.mp4 [92.5 MB]
11.requests模块-verify参数与ca证书_.mp4 [44.1 MB]
14.requests模块-session_.mp4 [19.8 MB]
2.requests模块-响应对象的text与content之间的区别_.mp4 [49.6 MB]
3.requests模块-响应对象常用的参数和方法_.mp4 [39.5 MB]
9.requests模块-timeout参数_.mp4 [32.5 MB]
4.requests模块-发送带请求头的请求_.mp4 [92.9 MB]
10.requests模块-代理proxies使用_.mp4 [128.1 MB]
15.案例-github模拟登陆_.mp4 [270.1 MB]
1.requests模块-简介-安装-使用_.mp4 [52.2 MB]
13.requests-post数据来源_.mp4 [199.7 MB]
5.requests模块-发送带参数的请求_.mp4 [107.8 MB]
📁 05_反爬与反反爬
14.js解析-js2py使用_.pcwlenv [30.3 MB]
10.chrome浏览器的使用_.pcwlenv [28.6 MB]
18.有道翻译实现_.pcwlenv [40.4 MB]
03.反爬与反反爬-常见概念与反爬方向_.pcwlenv [10.5 MB]
16.有道翻译分析_.pcwlenv [31.8 MB]
15.js解析-人人网登陆_.pcwlenv [55.9 MB]
07.验证码-验证码的知识_.pcwlenv [9.7 MB]
11.js解析-人人网登录分析_.pcwlenv [24.5 MB]
06.反爬与反反爬-基于数据加密进行反爬_.pcwlenv [40.0 MB]
04.反爬与反反爬-基于身份识别的反爬_.pcwlenv [14.4 MB]
02.反爬与反反爬-什么样的爬虫会被反_.pcwlenv [7.5 MB]
13.js解析-js代码分析_.pcwlenv [31.3 MB]
08.验证码-图像识别引擎_.pcwlenv [20.7 MB]
09.验证码-打码平台_.pcwlenv [41.5 MB]
12.js解析-定位js文件_.pcwlenv [24.7 MB]
01.反爬与反反爬-反爬原因_.pcwlenv [7.5 MB]
17.hashlib使用_.pcwlenv [37.3 MB]
05.反爬与反反爬-及与爬虫行为的反爬_.pcwlenv [40.2 MB]
📁 04阶段-项目部署和管理
📁 03-Django项目美多商城-第03天
📁 03-Django项目美多商城-第03天
📁 04-Django项目美多商城-第04天
📁 04-Django项目美多商城-第04天
📁 06-Django项目美多商城-第06天
📁 06-Django项目美多商城-第06天
📁 12-Django项目美多商城-第12天
📁 12-Django项目美多商城-第12天
📁 11-Django项目美多商城-第11天
📁 11-Django项目美多商城-第11天
📁 09-Django项目美多商城-第09天
📁 09-Django项目美多商城-第09天
📁 14-Django项目美多商城-第14天
📁 14-Django项目美多商城-第14天
📁 07-Django项目美多商城-第07天
📁 07-Django项目美多商城-第07天
📁 02-Django项目美多商城-第02天
📁 02-Django项目美多商城-第02天
📁 01-Django项目美多商城-第01天
📁 01-Django项目美多商城-第01天
📁 10-Django项目美多商城-第10天
📁 10-Django项目美多商城-第10天
📁 13-Django项目美多商城-第13天
📁 13-Django项目美多商城-第13天
📁 08-Django项目美多商城-第08天
📁 08-Django项目美多商城-第08天
📁 05-Django项目美多商城-第05天
📁 05-Django项目美多商城-第05天
📁 08_数据分析课程
📁 推荐系统项目2
📁 黑马头条推荐第九天
📁 02_课件
📁 03_代码
📁 toutiao_project
📁 scheduler
update.py [1.1 KB]
main.py [1.3 KB]
📁 .idea
📁 dictionaries
huxinghui.xml [88.0 B]
📁 inspectionProfiles
Project_Default.xml [790.0 B]
encodings.xml [135.0 B]
remote-mappings.xml [491.0 B]
toutiao_project.iml [603.0 B]
misc.xml [852.0 B]
modules.xml [282.0 B]
deployment.xml [771.0 B]
workspace.xml [56.9 KB]
📁 reco_sys
📁 online
online_update.py [5.7 KB]
__init__.py [1.1 KB]
📁 setting
logging.py [1.2 KB]
default.py [2.4 KB]
📁 server
recall_service.py [4.0 KB]
utils.py [4.0 KB]
__init__.py [925.0 B]
reco_centor.py [12.2 KB]
sort_service.py [3.1 KB]
redis_cache.py [3.9 KB]
📁 offline
📁 full_cal
📁 .ipynb_checkpoints
word2vec-checkpoint.ipynb [72.0 B]
merge_data-checkpoint.ipynb [72.0 B]
lr_sort-checkpoint.ipynb [72.0 B]
online_sort-checkpoint.ipynb [72.0 B]
update_recall-checkpoint.ipynb [26.5 KB]
user_profile-checkpoint.ipynb [72.0 B]
lr_sort.ipynb [189.9 KB]
merge_data.ipynb [46.2 KB]
word2vec.ipynb [25.7 KB]
online_sort.ipynb [9.0 KB]
update_recall.ipynb [30.5 KB]
user_profile.ipynb [20.8 KB]
📁 models
📁 tmp
📁 summary
📁 linear
…（层级过深，已停止）
events.out.tfevents.1561766113.hadoop-master [650.0 B]
events.out.tfevents.1561764557.hadoop-master [690.0 B]
events.out.tfevents.1561765617.hadoop-master [650.0 B]
📁 ckpt
📁 linear
…（层级过深，已停止）
📁 data
adult.test [1.7 MB]
adult.data [3.4 MB]
📁 ckpt
📁 text_embedding
model.ckpt-2557167.data-00000-of-00002 [1.9 MB]
checkpoint [289.0 B]
model.ckpt-2557167.meta [19.4 MB]
model.ckpt-2817137.index [575.0 B]
model.ckpt-2636266.index [575.0 B]
model.ckpt-2466253.meta [19.4 MB]
model.ckpt-2636266.data-00001-of-00002 [40.6 KB]
model.ckpt-2726691.data-00000-of-00002 [1.9 MB]
model.ckpt-2557167.data-00001-of-00002 [40.6 KB]
model.ckpt-2636266.meta [19.4 MB]
model.ckpt-2726691.index [575.0 B]
model.ckpt-2817137.meta [19.4 MB]
graph.pbtxt [73.5 MB]
model.ckpt-2557167.index [575.0 B]
model.ckpt-2466253.data-00001-of-00002 [40.6 KB]
model.ckpt-2726691.meta [19.4 MB]
model.ckpt-2466253.data-00000-of-00002 [1.9 MB]
model.ckpt-2817137.data-00000-of-00002 [1.9 MB]
events.out.tfevents.1561869077.hadoop-master [148.8 MB]
model.ckpt-2726691.data-00001-of-00002 [40.6 KB]
model.ckpt-2817137.data-00001-of-00002 [40.6 KB]
model.ckpt-2466253.index [575.0 B]
model.ckpt-2636266.data-00000-of-00002 [1.9 MB]
demo.py [5.6 KB]
ctr_train_20190706.tfrecords [3.5 MB]
nn_text_classification.py [2.2 KB]
train_ctr_20190605.tfrecords [3.5 MB]
census_example.py [3.7 KB]
census_predict.py [10.6 KB]
update_feature.py [4.7 KB]
hbaset.py [536.0 B]
update_article.py [12.5 KB]
__init__.py [2.4 KB]
update_user.py [9.3 KB]
update_recall.py [9.5 KB]
text_class.py [2.3 KB]
📁 abtest
user_reco_pb2_grpc.py [2.1 KB]
user_reco_pb2.py [11.8 KB]
grpc_test.py [1.7 KB]
user_reco.proto [738.0 B]
routing.py [6.0 KB]
📁 scripts
start_kafka.sh [498.0 B]
collect_click.sh [302.0 B]
import_incremental.sh [2.0 KB]
📁 更新到20190706
📁 day02
section10.html [38.7 KB]
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index.html [39.0 KB]
📁 day07
section6.html [38.7 KB]
section3.html [74.5 KB]
section7.html [38.7 KB]
section2.html [346.2 KB]
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index.html [38.7 KB]
📁 day01
index.html [38.9 KB]
section2.html [47.5 KB]
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section1.html [67.6 KB]
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📁 day05
section2.html [55.7 KB]
section1.html [48.7 KB]
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📁 reco
section2.html [41.0 KB]
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index.html [38.8 KB]
📁 day06
index.html [38.8 KB]
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section2.html [57.5 KB]
📁 day04
section3.html [75.8 KB]
section1.html [68.0 KB]
section6.html [69.0 KB]
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index.html [38.8 KB]
section7.html [38.7 KB]
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section4.html [88.6 KB]
📁 gitbook
📁 fonts
📁 fontawesome
fontawesome-webfont(1).eot [70.8 KB]
fontawesome-webfont.svg [247.5 KB]
FontAwesome.otf [73.4 KB]
fontawesome-webfont.ttf [138.2 KB]
fontawesome-webfont.woff [81.8 KB]
📁 plugins
📁 gitbook-plugin-katex
📁 fonts
KaTeX_Main-Regular.ttf [66.4 KB]
KaTeX_SansSerif-Italic.woff [17.7 KB]
KaTeX_Math-Regular.woff [23.2 KB]
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KaTeX_Math-Regular.woff2 [19.9 KB]
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KaTeX_Script-Regular.woff2 [12.0 KB]
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KaTeX_Main-Regular.eot [66.6 KB]
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KaTeX_Size1-Regular.ttf [12.9 KB]
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KaTeX_Math-BoldItalic.woff [22.6 KB]
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KaTeX_SansSerif-Italic.eot [30.6 KB]
KaTeX_Size2-Regular.ttf [12.1 KB]
KaTeX_Main-Regular.woff [36.7 KB]
KaTeX_Size3-Regular.woff2 [3.8 KB]
KaTeX_Main-Italic.woff [24.3 KB]
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KaTeX_Fraktur-Bold.eot [35.4 KB]
KaTeX_SansSerif-Bold.eot [33.4 KB]
KaTeX_Main-Italic.ttf [42.9 KB]
KaTeX_Fraktur-Regular.woff2 [19.4 KB]
katex.min.css [20.5 KB]
📁 gitbook-plugin-search
lunr.min.js [14.7 KB]
search.js [3.4 KB]
search.css [599.0 B]
📁 gitbook-plugin-sharing
buttons.js [2.9 KB]
📁 gitbook-plugin-expandable-chapters-small
expandable-chapters-small.js [2.0 KB]
expandable-chapters-small.css [580.0 B]
📁 gitbook-plugin-fontsettings
buttons.js [3.9 KB]
website.css [8.4 KB]
📁 gitbook-plugin-livereload
plugin.js [327.0 B]
📁 gitbook-plugin-highlight
website.css [30.0 KB]
ebook.css [2.7 KB]
📁 images
favicon.ico [4.2 KB]
apple-touch-icon-precomposed-152.png [90.6 KB]
style.css [38.3 KB]
app.js [741.5 KB]
📁 day08
section2.html [85.7 KB]
section4.html [121.3 KB]
section9.html [53.3 KB]
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📁 images
用户画像流程作用.png [68.8 KB]
原始ALS数据.png [150.3 KB]
每个词个数.png [55.1 KB]
flume外部结构.png [89.1 KB]
relu.png [23.3 KB]
index关系结构.png [293.7 KB]
黑马头条宣传.png [761.2 KB]
lookup.png [24.0 KB]
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感知机.png [21.6 KB]
类型变换.png [68.6 KB]
特征处理feature_column.png [709.8 KB]
PR公式.png [18.0 KB]
鸢尾花网络模型.png [216.9 KB]
CBOW模型.png [38.4 KB]
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profucer写数据过程.png [221.7 KB]
投影公式.png [9.2 KB]
spark启动好的.png [350.4 KB]
训练样本特正处理3.png [372.9 KB]
PC.png [311.3 KB]
loadbalance.png [463.9 KB]
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词表.png [155.1 KB]
深度学习CTR演化关系图.png [214.6 KB]
计算关键词中间结果.png [120.9 KB]
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PR计算图.png [103.0 KB]
tfidf结果.png [124.6 KB]
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cbow推导过程.png [92.1 KB]
TF动态图.gif [38.0 KB]
playground.png [34.1 KB]
多agent.png [250.0 KB]
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kafka架构.png [215.0 KB]
固定值张量.png [109.5 KB]
m个样本的循环浅层.png [221.5 KB]
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区别.png [162.8 KB]
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复杂数据1.png [72.9 KB]
识别输出概率.png [166.5 KB]
交叉熵损失公式.png [22.7 KB]
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LSH官方图.png [380.6 KB]
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数据流图.png [164.2 KB]
大数定律求解.png [70.9 KB]
tfdataset格式.png [65.3 KB]
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hadoopwv目录.png [228.8 KB]
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损失函数图.png [126.9 KB]
replica.png [153.4 KB]
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用户原始数据.png [96.8 KB]
单层感知机.png [47.8 KB]
基础用户画像.png [62.7 KB]
关联推荐结果.png [233.7 KB]
数据倾斜方案1.png [717.5 KB]
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直线方程.png [12.0 KB]
复杂两类数据分类1.png [96.4 KB]
kafka.png [36.8 KB]
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浅层网络的标记.png [272.2 KB]
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运行的APP.png [357.1 KB]
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📁 day03
section9.html [38.7 KB]
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search_index.json [11.7 MB]
index.html [39.8 KB]
📁 04_资料
📁 第九天课程总结.mindnode
📁 resources
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._9C661AC4-A7DA-4D2A-B4D5-2A3C81292642.png [4.0 KB]
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D7CC91D9-118B-4C90-86FB-A05FD4435A9E.png [251.2 KB]
📁 QuickLook
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📁 style.mindnodestyle
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耗时整理‖免费分享 cunlove.cn.png [4.0 KB]
QQ20190706-163344@2x.png [352.7 KB]
._QQ20190706-164316@2x.png [4.0 KB]
._第九天课堂纪要.pdf [4.0 KB]
QQ20190706-111407@2x.png [618.3 KB]
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第九天课堂纪要.md [11.1 KB]
QQ20190706-115233@2x.png [406.8 KB]
QQ20190706-164316@2x.png [587.4 KB]
._QQ20190706-112138@2x.png [4.0 KB]
QQ20190706-120031@2x.png [397.2 KB]
在线最优化求解(Online Optimization)-冯扬.pdf [961.1 KB]
._QQ20190706-151711@2x.png [4.0 KB]
._第九天课程总结.mindnode [4.0 KB]
._QQ20190706-163344@2x.png [4.0 KB]
._在线最优化求解(Online Optimization)-冯扬.pdf [4.0 KB]
._QQ20190706-120031@2x.png [4.0 KB]
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._第九天课堂纪要.md [4.0 KB]
QQ20190706-112138@2x.png [338.7 KB]
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📁 01_视频
02_tf.data_.mp4 [53.2 MB]
06_wor2vec的前向计算与反向传播计算_.mp4 [43.2 MB]
11_传统CTR排序演化图以及介绍_.mp4 [20.9 MB]
01_复习_.mp4 [73.7 MB]
05_word2vec介绍_.mp4 [5.7 MB]
13_特征交叉与分桶_.mp4 [21.7 MB]
09_黑马头条训练样本存储tfrecords1_.mp4 [78.5 MB]
03_tf.feature_column_.mp4 [28.6 MB]
12_传统CTR排序演化图以及介绍2_.mp4 [57.2 MB]
15_总结_.mp4 [38.8 MB]
08_tfrecords文件深度训练流程方案_.mp4 [31.9 MB]
04_统计与神经网络语言模型_.mp4 [91.2 MB]
14_特征交叉与分桶案例_.mp4 [35.1 MB]
10_黑马头条训练样本存储tfrecords2_.mp4 [34.5 MB]
07_文本分类案例与词向量观察_.mp4 [105.1 MB]
📁 黑马头条推荐第八天
📁 02_课件
📁 最新课件到20190704
📁 day03
section9.html [38.3 KB]
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section2.html [102.2 KB]
section3.html [95.4 KB]
section5.html [65.9 KB]
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📁 day01
section8.html [38.3 KB]
section2.html [47.1 KB]
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section0.html [67.8 KB]
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📁 day08
section9.html [38.3 KB]
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📁 reco
index.html [38.4 KB]
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📁 day04
index.html [38.4 KB]
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📁 gitbook
📁 plugins
📁 gitbook-plugin-highlight
ebook.css [2.7 KB]
website.css [30.0 KB]
📁 gitbook-plugin-search
search.css [599.0 B]
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📁 gitbook-plugin-expandable-chapters-small
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📁 gitbook-plugin-livereload
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📁 gitbook-plugin-fontsettings
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KaTeX_Size4-Regular.woff2 [5.1 KB]
KaTeX_Fraktur-Bold.woff2 [20.0 KB]
KaTeX_Math-BoldItalic.eot [39.1 KB]
KaTeX_Size3-Regular.ttf [8.2 KB]
KaTeX_Math-Regular.woff2 [19.9 KB]
KaTeX_AMS-Regular.ttf [69.8 KB]
KaTeX_AMS-Regular.eot [70.0 KB]
KaTeX_Fraktur-Regular.eot [34.1 KB]
KaTeX_Size3-Regular.woff [4.7 KB]
KaTeX_Math-Regular.woff [23.2 KB]
KaTeX_Size2-Regular.ttf [12.1 KB]
KaTeX_Main-Bold.ttf [59.1 KB]
KaTeX_Caligraphic-Bold.woff [11.9 KB]
KaTeX_Caligraphic-Bold.ttf [19.1 KB]
KaTeX_Caligraphic-Bold.eot [19.4 KB]
KaTeX_SansSerif-Italic.woff [17.7 KB]
KaTeX_Math-BoldItalic.woff [22.6 KB]
KaTeX_Fraktur-Bold.woff [22.8 KB]
KaTeX_Main-Bold.woff2 [28.8 KB]
KaTeX_Math-Italic.woff2 [20.0 KB]
KaTeX_Math-Regular.eot [40.6 KB]
KaTeX_Size1-Regular.ttf [12.9 KB]
KaTeX_Fraktur-Regular.woff [22.3 KB]
KaTeX_Caligraphic-Regular.eot [18.8 KB]
KaTeX_Size4-Regular.woff [6.3 KB]
KaTeX_SansSerif-Regular.ttf [29.3 KB]
KaTeX_Main-Regular.woff2 [30.5 KB]
KaTeX_Main-Italic.woff [24.3 KB]
KaTeX_Size1-Regular.eot [13.1 KB]
KaTeX_Main-Italic.eot [43.1 KB]
KaTeX_Size4-Regular.ttf [11.0 KB]
KaTeX_Math-Regular.ttf [40.3 KB]
KaTeX_SansSerif-Regular.woff2 [13.6 KB]
KaTeX_Math-BoldItalic.woff2 [19.6 KB]
KaTeX_Script-Regular.ttf [24.3 KB]
KaTeX_Main-Regular.ttf [66.4 KB]
KaTeX_AMS-Regular.woff [39.3 KB]
KaTeX_Typewriter-Regular.ttf [34.7 KB]
KaTeX_Main-Regular.eot [66.6 KB]
KaTeX_Script-Regular.eot [24.5 KB]
KaTeX_Caligraphic-Regular.ttf [18.5 KB]
KaTeX_Caligraphic-Regular.woff2 [10.2 KB]
katex.min.css [20.5 KB]
📁 images
favicon.ico [4.2 KB]
apple-touch-icon-precomposed-152.png [90.6 KB]
📁 fonts
📁 fontawesome
fontawesome-webfont.woff [81.8 KB]
fontawesome-webfont.eot [70.8 KB]
fontawesome-webfont.svg [247.5 KB]
fontawesome-webfont.ttf [138.2 KB]
FontAwesome.otf [73.4 KB]
app.js [741.5 KB]
style.css [38.3 KB]
📁 day07
section4.html [49.4 KB]
section3.html [174.3 KB]
section2.html [345.8 KB]
section6.html [38.3 KB]
index.html [38.3 KB]
section5.html [47.4 KB]
section1(1).html [59.7 KB]
section7.html [38.3 KB]
📁 day05
index.html [38.4 KB]
section2.html [55.3 KB]
section1.html [48.3 KB]
📁 day02
section2.html [75.2 KB]
section10.html [38.3 KB]
section6.html [59.9 KB]
section3.html [47.7 KB]
section9.html [38.3 KB]
section4.html [62.7 KB]
section7.html [62.5 KB]
index.html [38.5 KB]
section8.html [67.2 KB]
section1.html [53.5 KB]
section5.html [53.4 KB]
📁 images
a方图.png [16.5 KB]
TF构建流程.png [508.1 KB]
profucer写数据过程.png [221.7 KB]
tfidf结果.png [124.6 KB]
hash列.png [338.7 KB]
用户关联结果2.png [160.0 KB]
词向量解释1.png [178.9 KB]
浅层网络的标记.png [272.2 KB]
固定值张量.png [109.5 KB]
softmax计算案例.png [103.4 KB]
直线图.png [16.1 KB]
sqoop导入hadoop文件数据.png [128.8 KB]
pycharm远程连接.png [178.3 KB]
词向量可视化效果.png [219.6 KB]
PR公式.png [18.0 KB]
relu.png [23.3 KB]
hbase启动好的.png [224.2 KB]
表截图.png [106.3 KB]
textrank词性.png [480.4 KB]
TF动态图.gif [38.0 KB]
hadoop看sqoop.png [344.2 KB]
tensorflowgithub.png [164.5 KB]
flume实战.png [137.8 KB]
数据倾斜.png [1.0 MB]
OP名字修改.png [29.6 KB]
感知机公式.png [20.1 KB]
flume.png [110.6 KB]
TFIDF结果2.png [111.6 KB]
tanh.png [23.9 KB]
合并用户文章.png [200.1 KB]
推荐系统业务架构.png [328.5 KB]
TF最新架构图.png [557.7 KB]
hadoopwv目录.png [228.8 KB]
PC.png [311.3 KB]
wide&deep模型.png [289.2 KB]
flume参数.png [202.1 KB]
训练样本特征处理4.png [334.8 KB]
倾斜解决方案2.png [500.0 KB]
m个样本的循环浅层.png [221.5 KB]
rb概率.png [319.8 KB]
数据倾斜方案1.png [717.5 KB]
PR计算图.png [103.0 KB]
搜索兴趣度.png [182.6 KB]
类别词汇表.png [347.1 KB]
消费者设计.png [275.3 KB]
添加步骤.png [118.4 KB]
词向量公式.png [46.7 KB]
投影公式.png [9.2 KB]
目录结构1.png [19.2 KB]
LSH不同的地方.png [259.9 KB]
随机投影方式.png [715.9 KB]
flume外部结构.png [89.1 KB]
复杂两类数据分类.png [114.0 KB]
AB测试.png [186.3 KB]
ML与DL关系.png [445.8 KB]
tensors_flowing.gif [9.5 MB]
文章权重向量.png [153.4 KB]
网络优化动态图.gif [6.6 MB]
排序逻辑.png [293.6 KB]
minihash2.png [86.8 KB]
历史记录.png [106.1 KB]
用户文章不唯一.png [338.6 KB]
groupbykey.png [838.2 KB]
数据倾斜时间.png [518.3 KB]
排序模块.png [110.8 KB]
实时计算图.png [478.2 KB]
als公式.png [8.9 KB]
词的无向图.png [326.3 KB]
mappred.png [907.0 KB]
复杂两类数据分类1.png [96.4 KB]
导数计算图.png [29.8 KB]
流量切分.png [68.2 KB]
黑马头条宣传.png [761.2 KB]
训练样本特正处理3.png [372.9 KB]
复杂数据1.png [72.9 KB]
hadoop启动好的.png [248.7 KB]
brand.png [239.6 KB]
框架关注.png [136.2 KB]
FFM特征交叉.png [323.2 KB]
神经元.png [79.1 KB]
逻辑回归的计算图.png [47.3 KB]
FTRL共识.png [43.1 KB]
网络结构.png [113.6 KB]
召回读取服务.png [33.2 KB]
区别.png [162.8 KB]
年份分桶.png [184.0 KB]
leakyrelu.png [24.6 KB]
传播算法演示.png [171.7 KB]
交叉损失理解.png [121.1 KB]
单agent多sink.png [245.4 KB]
运行的APP.png [357.1 KB]
埋点流程.png [90.9 KB]
类型变换.png [68.6 KB]
用户原始数据.png [96.8 KB]
原始ALS数据.png [150.3 KB]
更新环境设置.png [209.6 KB]
spark运行原理过程.png [1012.4 KB]
黑马头条推荐流程图.png [214.7 KB]
流式计算.png [226.9 KB]
kafka文件.png [173.3 KB]
📁 day06
section4.html [75.4 KB]
section3.html [62.9 KB]
section6.html [65.5 KB]
section2.html [57.1 KB]
section8.html [38.3 KB]
section1.html [44.6 KB]
index.html [38.3 KB]
section7.html [38.3 KB]
section5.html [44.1 KB]
search_index.json [11.5 MB]
index.html [39.4 KB]
📁 04_资料
QQ20190704-161439@2x.png [341.9 KB]
._QQ20190704-161439@2x.png [4.0 KB]
QQ20190704-162026@2x.png [623.0 KB]
QQ20190704-172953@2x.png [369.8 KB]
._第八天课堂纪要.md [4.0 KB]
QQ20190704-104913@2x.png [1.2 MB]
._QQ20190704-164158@2x.png [4.0 KB]
第八天课堂纪要.md [9.0 KB]
第八天课堂纪要.pdf [267.1 KB]
耗时整理‖免费分享 cunlove.cn.png [4.0 KB]
._QQ20190704-104913@2x.png [4.0 KB]
._第八天课堂纪要.pdf [4.0 KB]
._QQ20190704-172953@2x.png [4.0 KB]
QQ20190704-164158@2x.png [235.2 KB]
📁 01_视频
07_训练与评估_.mp4 [16.9 MB]
05_LinearClassifier做分类_.mp4 [117.5 MB]
01_复习_.mp4 [27.2 MB]
08_神经网络基础_.mp4 [91.3 MB]
09_神金网络计算_.mp4 [21.6 MB]
10_神经网络分类、损失计算、链式法则_.mp4 [96.0 MB]
12_DNNclassifier做分类_.mp4 [49.4 MB]
02_变量观察与模型保存加载_.mp4 [60.1 MB]
11_向量化编程_.mp4 [66.3 MB]
04_命令行参数_.mp4 [17.5 MB]
06_特征列处理_.mp4 [45.9 MB]
03_模型保存加载_.mp4 [22.0 MB]
13_训练结果解释_.mp4 [5.0 MB]
📁 03_代码
📁 toutiao_project
📁 reco_sys
📁 offline
📁 models
📁 tmp
📁 ckpt
📁 linear
…（层级过深，已停止）
📁 summary
📁 linear
…（层级过深，已停止）
events.out.tfevents.1561764557.hadoop-master [690.0 B]
events.out.tfevents.1561766113.hadoop-master [650.0 B]
events.out.tfevents.1561765617.hadoop-master [650.0 B]
📁 data
adult.data [3.4 MB]
adult.test [1.7 MB]
census_example.py [3.7 KB]
demo.py [5.6 KB]
census_predict.py [7.7 KB]
📁 full_cal
📁 .ipynb_checkpoints
merge_data-checkpoint.ipynb [72.0 B]
merge_data.ipynb [46.2 KB]
update_recall.ipynb [30.5 KB]
online_sort.ipynb [9.0 KB]
lr_sort.ipynb [170.1 KB]
word2vec.ipynb [25.7 KB]
user_profile.ipynb [20.8 KB]
update_article.py [12.5 KB]
update_feature.py [4.7 KB]
update_user.py [9.3 KB]
__init__.py [2.4 KB]
update_recall.py [9.5 KB]
hbaset.py [536.0 B]
📁 setting
logging.py [1.2 KB]
default.py [2.4 KB]
📁 server
sort_service.py [3.1 KB]
redis_cache.py [3.9 KB]
utils.py [4.0 KB]
recall_service.py [4.0 KB]
reco_centor.py [12.2 KB]
__init__.py [925.0 B]
📁 abtest
user_reco_pb2_grpc.py [2.1 KB]
user_reco.proto [738.0 B]
routing.py [6.0 KB]
grpc_test.py [1.7 KB]
user_reco_pb2.py [11.8 KB]
📁 online
__init__(1).py [1.1 KB]
__init__.py [1.1 KB]
online_update(1).py [5.7 KB]
online_update.py [5.7 KB]
📁 .idea
📁 inspectionProfiles
Project_Default.xml [790.0 B]
📁 dictionaries
huxinghui(1).xml [88.0 B]
deployment.xml [771.0 B]
workspace.xml [57.7 KB]
remote-mappings.xml [491.0 B]
modules.xml [282.0 B]
toutiao_project.iml [603.0 B]
misc.xml [852.0 B]
encodings.xml [135.0 B]
📁 scripts
collect_click.sh [302.0 B]
import_incremental.sh [2.0 KB]
start_kafka.sh [498.0 B]
📁 scheduler
main.py [1.3 KB]
update.py [1.1 KB]
📁 黑马头条推荐第二天
📁 03_代码
📁 toutiao_project
📁 scheduler
update.py [351.0 B]
main.py [783.0 B]
📁 .idea
📁 inspectionProfiles
Project_Default.xml [790.0 B]
📁 dictionaries
huxinghui.xml [88.0 B]
workspace.xml [52.2 KB]
modules.xml [282.0 B]
encodings.xml [135.0 B]
toutiao_project.iml [603.0 B]
deployment.xml [771.0 B]
misc.xml [852.0 B]
remote-mappings.xml [491.0 B]
📁 reco_sys
📁 offline
📁 full_cal
📁 .ipynb_checkpoints
merge_data-checkpoint.ipynb [72.0 B]
merge_data.ipynb [46.2 KB]
update_article(1).py [8.4 KB]
__init__.py [1.4 KB]
📁 setting
logging.py [508.0 B]
📁 scripts
collect_click.sh [302.0 B]
import_incremental.sh [2.0 KB]
📁 01_视频
04_离线更新添加_.mp4 [74.7 MB]
03_文章画像计算存储_.mp4 [36.8 MB]
09_文章向量保存2_.mp4 [46.9 MB]
10_相似度计算介绍_.mp4 [24.9 MB]
12_相似度结果存储_.mp4 [42.0 MB]
02_文章关键词与主题词计算_.mp4 [58.7 MB]
06_word2vec介绍与词向量训练保存_.mp4 [97.3 MB]
01_作业讲解_.mp4 [65.8 MB]
11_LSH原理与实现_.mp4 [123.0 MB]
08_文章向量保存_.mp4 [42.4 MB]
07_文章向量计算_.mp4 [25.4 MB]
05_离线增量更新_.mp4 [23.1 MB]
📁 04_资料
📁 第二天总结.mindnode
📁 style.mindnodestyle
._metadata.plist [4.0 KB]
metadata.plist [395.0 B]
._contents.xml [4.0 KB]
contents.xml [6.2 KB]
📁 QuickLook
Preview.jpg [179.6 KB]
._Preview(1).jpg [4.0 KB]
._Preview.jpg [4.0 KB]
contents.xml [12.2 KB]
._contents.xml [4.0 KB]
viewState.plist [176.0 B]
._style.mindnodestyle [4.0 KB]
._QuickLook [4.0 KB]
._viewState.plist [4.0 KB]
._resources [4.0 KB]
QQ20190625-162654@2x.png [370.8 KB]
._QQ20190625-101733@2x.png [4.0 KB]
QQ20190625-151155@2x.png [243.2 KB]
第二天课堂纪要.md [10.1 KB]
._作业题答案.pdf [4.0 KB]
第二天课堂纪要.pdf [212.4 KB]
._QQ20190625-162654@2x.png [4.0 KB]
._第二天课堂纪要.md [4.0 KB]
._QQ20190625-173020@2x.png [4.0 KB]
作业题答案.pdf [432.0 KB]
._第二天总结.mindnode [4.0 KB]
._QQ20190625-151155@2x.png [4.0 KB]
._第二天课堂纪要.pdf [4.0 KB]
耗时整理‖免费分享 cunlove.cn.png [807.2 KB]
QQ20190625-101733@2x.png [61.7 KB]
📁 02_课件
📁 _book
📁 reco
section2.html [37.2 KB]
index.html [35.0 KB]
section1.html [39.8 KB]
📁 day06
section5.html [40.7 KB]
section3.html [59.5 KB]
section6.html [65.4 KB]
section2.html [53.7 KB]
section8.html [34.9 KB]
section1.html [41.2 KB]
section7.html [34.9 KB]
index.html [35.0 KB]
section4.html [71.6 KB]
📁 gitbook
📁 plugins(1)
📁 images
favicon.ico [4.2 KB]
apple-touch-icon-precomposed-152.png [90.6 KB]
📁 images(1)
📁 fonts
📁 fontawesome
fontawesome-webfont.svg [247.5 KB]
fontawesome-webfont.eot [70.8 KB]
fontawesome-webfont.ttf [138.2 KB]
fontawesome-webfont.woff [81.8 KB]
FontAwesome.otf [73.4 KB]
📁 plugins
📁 gitbook-plugin-search
lunr.min.js [14.7 KB]
search.js [3.4 KB]
search.css [599.0 B]
📁 gitbook-plugin-livereload
plugin.js [327.0 B]
📁 gitbook-plugin-expandable-chapters-small
expandable-chapters-small.js [2.0 KB]
expandable-chapters-small.css [580.0 B]
📁 gitbook-plugin-katex
📁 fonts
KaTeX_SansSerif-Regular.woff2 [13.6 KB]
KaTeX_Size1-Regular.ttf [12.9 KB]
KaTeX_SansSerif-Regular.eot [29.5 KB]
KaTeX_Main-Regular.ttf [66.4 KB]
KaTeX_Math-BoldItalic.eot [39.1 KB]
KaTeX_Script-Regular.woff2 [12.0 KB]
KaTeX_Caligraphic-Regular.woff [11.6 KB]
KaTeX_SansSerif-Italic.eot [30.6 KB]
KaTeX_Main-Regular.woff [36.7 KB]
KaTeX_AMS-Regular.ttf [69.8 KB]
KaTeX_Math-BoldItalic.ttf [38.8 KB]
KaTeX_Main-Bold.woff2 [28.8 KB]
KaTeX_Caligraphic-Regular.woff2 [10.2 KB]
KaTeX_Typewriter-Regular.woff2 [16.9 KB]
KaTeX_Typewriter-Regular.woff [20.2 KB]
KaTeX_Size4-Regular.ttf [11.0 KB]
KaTeX_Fraktur-Bold.woff2 [20.0 KB]
KaTeX_Size2-Regular.ttf [12.1 KB]
KaTeX_Script-Regular.eot [24.5 KB]
KaTeX_AMS-Regular.eot [70.0 KB]
KaTeX_Main-Bold.woff [34.6 KB]
KaTeX_Size3-Regular.woff [4.7 KB]
KaTeX_SansSerif-Regular.woff [16.4 KB]
KaTeX_Math-BoldItalic.woff2 [19.6 KB]
KaTeX_Main-Italic.woff [24.3 KB]
KaTeX_Math-Regular.ttf [40.3 KB]
KaTeX_Size1-Regular.woff [6.8 KB]
KaTeX_AMS-Regular.woff2 [32.4 KB]
KaTeX_Caligraphic-Regular.ttf [18.5 KB]
KaTeX_Math-Regular.eot [40.6 KB]
KaTeX_AMS-Regular.woff [39.3 KB]
KaTeX_SansSerif-Italic.woff2 [14.8 KB]
KaTeX_Caligraphic-Bold.woff [11.9 KB]
KaTeX_Math-Italic.woff2 [20.0 KB]
KaTeX_Math-Regular.woff2 [19.9 KB]
KaTeX_Math-BoldItalic.woff [22.6 KB]
KaTeX_Size4-Regular.woff [6.3 KB]
KaTeX_Size2-Regular.eot [12.4 KB]
KaTeX_Main-Bold.ttf [59.1 KB]
KaTeX_Size3-Regular.eot [8.4 KB]
KaTeX_SansSerif-Italic.ttf [30.3 KB]
KaTeX_SansSerif-Regular.ttf [29.3 KB]
KaTeX_Size2-Regular.woff [6.5 KB]
KaTeX_Main-Regular.woff2 [30.5 KB]
KaTeX_Main-Italic.ttf [42.9 KB]
KaTeX_Fraktur-Bold.ttf [35.1 KB]
KaTeX_Caligraphic-Bold.woff2 [10.4 KB]
KaTeX_Caligraphic-Bold.ttf [19.1 KB]
KaTeX_Main-Italic.woff2 [20.5 KB]
KaTeX_Size2-Regular.woff2 [5.4 KB]
KaTeX_SansSerif-Bold.woff [18.7 KB]
KaTeX_Main-Bold.eot [59.3 KB]
KaTeX_Size4-Regular.woff2 [5.1 KB]
KaTeX_Size3-Regular.woff2 [3.8 KB]
KaTeX_Fraktur-Bold.eot [35.4 KB]
KaTeX_SansSerif-Bold.eot [33.4 KB]
KaTeX_Math-Italic.eot [40.7 KB]
KaTeX_Size1-Regular.eot [13.1 KB]
KaTeX_SansSerif-Bold.woff2 [15.6 KB]
KaTeX_Main-Italic.eot [43.1 KB]
KaTeX_Size4-Regular.eot [11.3 KB]
KaTeX_SansSerif-Bold.ttf [33.2 KB]
KaTeX_Math-Italic.ttf [40.5 KB]
KaTeX_Caligraphic-Bold.eot [19.4 KB]
KaTeX_Size1-Regular.woff2 [5.7 KB]
KaTeX_Math-Italic.woff [23.3 KB]
KaTeX_Fraktur-Bold.woff [22.8 KB]
KaTeX_Script-Regular.ttf [24.3 KB]
KaTeX_Main-Regular.eot [66.6 KB]
KaTeX_Math-Regular.woff [23.2 KB]
KaTeX_Script-Regular.woff [13.5 KB]
KaTeX_Fraktur-Regular.woff [22.3 KB]
KaTeX_Caligraphic-Regular.eot [18.8 KB]
KaTeX_Size3-Regular.ttf [8.2 KB]
KaTeX_Typewriter-Regular.ttf [34.7 KB]
KaTeX_Fraktur-Regular.eot [34.1 KB]
KaTeX_SansSerif-Italic.woff [17.7 KB]
KaTeX_Fraktur-Regular.ttf [33.8 KB]
KaTeX_Fraktur-Regular.woff2 [19.4 KB]
KaTeX_Typewriter-Regular.eot [34.9 KB]
katex.min.css [20.5 KB]
📁 gitbook-plugin-fontsettings
buttons.js [3.9 KB]
website.css [8.4 KB]
📁 gitbook-plugin-sharing
buttons.js [2.9 KB]
📁 gitbook-plugin-highlight
ebook.css [2.7 KB]
website.css [30.0 KB]
📁 fonts(1)
app(1).js [741.5 KB]
app.js [741.5 KB]
style(1).css [38.3 KB]
style.css [38.3 KB]
📁 day03
section1.html [43.2 KB]
section4.html [34.9 KB]
section3.html [52.2 KB]
index.html [35.0 KB]
section2.html [60.4 KB]
section0.html [36.1 KB]
section5.html [34.9 KB]
📁 day05
index.html [35.0 KB]
section1.html [43.8 KB]
section2.html [47.6 KB]
📁 images
神经网络如何分类.png [126.4 KB]
随机值张量.png [126.8 KB]
LSH官方图.png [380.6 KB]
中间计算结果.png [185.8 KB]
LSH不同的地方.png [259.9 KB]
基础用户画像.png [62.7 KB]
合并用户文章.png [200.1 KB]
埋点流程.png [90.9 KB]
推荐系统业务架构.png [328.5 KB]
模型存放目录.png [129.0 KB]
数据量.png [76.6 KB]
ROC曲线.png [64.1 KB]
特征处理feature_column.png [709.8 KB]
hadoopwv目录.png [228.8 KB]
TF最新架构图.png [557.7 KB]
召回排序.png [79.0 KB]
用户画像流程作用.png [21.4 KB]
用户主题词爆炸.png [229.6 KB]
鸢尾花网络模型.png [216.9 KB]
minihash.png [88.1 KB]
数据流图.png [164.2 KB]
词的无向图.png [326.3 KB]
Textrank原理.png [56.2 KB]
历史记录.png [106.1 KB]
目录结构1.png [19.2 KB]
add图.png [58.7 KB]
类型变换.png [68.6 KB]
感知机公式.png [43.0 KB]
hbase启动好的.png [224.2 KB]
排序逻辑.png [293.6 KB]
投影公式.png [9.2 KB]
交叉损失理解.png [121.1 KB]
复杂数据1.png [180.9 KB]
flume第一次收集.png [106.4 KB]
关联推荐结果.png [233.7 KB]
word2vecnn.png [119.6 KB]
playground两类.png [99.8 KB]
als打分矩阵.png [104.7 KB]
推荐系统后台.png [217.6 KB]
类别词汇表.png [347.1 KB]
abtest与推荐中心逻辑.png [75.3 KB]
FFM特征交叉.png [323.2 KB]
实时排序逻辑.png [102.0 KB]
推荐架构.png [407.9 KB]
tfdataset格式.png [65.3 KB]
hash列.png [338.7 KB]
softmax公式.png [27.9 KB]
TF动态图.gif [38.0 KB]
召回排序结构.png [172.9 KB]
黑马头条推荐流程图.png [214.7 KB]
训练样本前期特征.png [267.6 KB]
感知机.png [49.8 KB]
交叉熵损失公式.png [22.7 KB]
鸢尾花.png [3.4 MB]
类型.png [108.1 KB]
阶.png [45.8 KB]
无向图分数计算.png [310.9 KB]
神经元.png [247.6 KB]
固定值张量.png [109.5 KB]
textrank词性.png [480.4 KB]
用户关联结果2.png [160.0 KB]
AB测试.png [186.3 KB]
传播算法演示.png [171.7 KB]
softmax回归.png [112.2 KB]
softmax展开.png [58.3 KB]
流量切分.png [68.2 KB]
playground.png [34.1 KB]
在线目录.png [14.1 KB]
PR计算图.png [103.0 KB]
网页pagerank.png [570.7 KB]
处理类型个数.png [744.3 KB]
复杂两类数据分类1.png [96.4 KB]
LR.png [148.0 KB]
OP名字修改.png [29.6 KB]
训练样本特正处理3.png [372.9 KB]
TFAPI.png [99.2 KB]
tensorflow.png [188.9 KB]
原始ALS数据.png [150.3 KB]
词向量解释1.png [178.9 KB]
框架关注.png [136.2 KB]
计算关键词中间结果.png [120.9 KB]
文章权重向量.png [153.4 KB]
特征处理原则.png [94.4 KB]
records.png [247.0 KB]
pycharm远程连接.png [178.3 KB]
添加步骤.png [118.4 KB]
原始日志数据.png [290.8 KB]
catidentity.png [340.5 KB]
hadoop看sqoop.png [344.2 KB]
复杂数据2.png [247.3 KB]
minihash2.png [86.8 KB]
Tensorboard.png [35.1 KB]
tensorflowgithub.png [90.2 KB]
FTRL共识.png [43.1 KB]
用户文章不唯一.png [338.6 KB]
als公式.png [8.9 KB]
画像业务.png [112.1 KB]
推荐目录.png [73.7 KB]
serving图.png [139.2 KB]
梯度下降理解.png [57.8 KB]
📁 day07
section2.html [61.9 KB]
section10.html [40.6 KB]
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section1.html [65.0 KB]
index.html [35.0 KB]
📁 day01
section2.html [43.7 KB]
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index.html [35.0 KB]
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📁 day02
section9.html [34.9 KB]
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📁 day04
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search_index.json [7.7 MB]
index.html [36.0 KB]
📁 黑马头条推荐第四天
📁 03_代码
📁 toutiao_project
📁 scripts
collect_click.sh [302.0 B]
import_incremental.sh [2.0 KB]
📁 .idea
📁 dictionaries
huxinghui.xml [88.0 B]
📁 inspectionProfiles
Project_Default.xml [790.0 B]
toutiao_project.iml [603.0 B]
remote-mappings.xml [491.0 B]
modules.xml [282.0 B]
deployment.xml [771.0 B]
misc.xml [852.0 B]
encodings.xml [135.0 B]
workspace.xml [54.3 KB]
📁 reco_sys
📁 offline
📁 full_cal
📁 .ipynb_checkpoints
merge_data-checkpoint.ipynb [72.0 B]
lr_sort.ipynb [170.1 KB]
user_profile.ipynb [20.8 KB]
merge_data.ipynb [46.2 KB]
update_recall.ipynb [30.5 KB]
word2vec.ipynb [25.7 KB]
update_article.py [12.5 KB]
__init__.py [2.4 KB]
update_user.py [9.3 KB]
update_feature.py [4.7 KB]
hbaset.py [536.0 B]
update_recall.py [9.5 KB]
📁 setting
logging.py [508.0 B]
📁 scheduler
main.py [1.3 KB]
update.py [1.1 KB]
📁 04_资料
📁 离线表设计总结.mindnode
📁 style.mindnodestyle
contents.xml [6.2 KB]
metadata.plist [395.0 B]
📁 resources
📁 QuickLook
Preview.jpg [236.0 KB]
viewState.plist [178.0 B]
contents.xml [14.7 KB]
第四天课堂纪要.pdf [191.8 KB]
第四天课堂纪要.md [4.8 KB]
作业题答案.md [3.6 KB]
耗时整理‖免费分享 cunlove.cn.png [847.2 KB]
QQ20190627-230444@2x.png [253.9 KB]
QQ20190628-110729@2x.png [752.7 KB]
📁 01_视频
02_基于内容召回_.mp4 [79.1 MB]
06_模型训练3_.mp4 [35.3 MB]
07_模型问题解决与特征中心_.mp4 [58.9 MB]
11_离线任务总结_.mp4 [11.6 MB]
03_离线召回定时更新_.mp4 [20.2 MB]
01_复习_.mp4 [69.2 MB]
09_用户特征中心存储_.mp4 [21.9 MB]
08_模型预测结果_.mp4 [35.1 MB]
04_模型训练1_.mp4 [84.3 MB]
05_模型训练2_.mp4 [137.3 MB]
12_实时计算业务介绍_.mp4 [42.3 MB]
10_特征中心定时更新_.mp4 [23.7 MB]
📁 02_课件
📁 最新课件到20190628
📁 day04
section3.html [76.7 KB]
index.html [35.4 KB]
section1.html [64.6 KB]
section6.html [65.6 KB]
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section5.html [53.2 KB]
section0.html [37.1 KB]
section2.html [47.9 KB]
section4.html [84.2 KB]
📁 day03
section6.html [35.3 KB]
index.html [35.4 KB]
section3.html [43.6 KB]
section5.html [52.6 KB]
section2.html [78.6 KB]
section7.html [35.3 KB]
section1.html [46.2 KB]
section4.html [60.8 KB]
📁 day01
section8.html [35.3 KB]
section1.html [64.2 KB]
section4.html [72.9 KB]
index.html [35.4 KB]
section9.html [35.3 KB]
section0.html [64.8 KB]
section3.html [119.7 KB]
section6.html [97.0 KB]
section7.html [46.9 KB]
section2.html [44.1 KB]
section5.html [45.6 KB]
📁 day06
section3.html [60.0 KB]
section6.html [65.8 KB]
section8.html [35.3 KB]
section2.html [54.1 KB]
section5.html [41.1 KB]
section1.html [41.6 KB]
section4.html [72.0 KB]
section7.html [35.3 KB]
index.html [35.4 KB]
📁 day07
section8.html [44.4 KB]
section11.html [49.9 KB]
section10.html [41.0 KB]
section2.html [62.3 KB]
section3.html [55.2 KB]
section4.html [48.7 KB]
section7.html [117.9 KB]
index.html [35.5 KB]
section6.html [49.9 KB]
section13.html [35.1 KB]
section12.html [35.3 KB]
section5.html [66.6 KB]
section9.html [40.7 KB]
section1.html [65.4 KB]
📁 day02
section3.html [44.7 KB]
section1.html [50.5 KB]
section10.html [35.3 KB]
section4.html [59.7 KB]
section7.html [59.6 KB]
section5.html [50.6 KB]
section6.html [56.9 KB]
section9.html [35.3 KB]
section8.html [64.2 KB]
index.html [35.6 KB]
section2(1).html [72.3 KB]
📁 gitbook
📁 plugins
📁 gitbook-plugin-search
search.css [599.0 B]
lunr.min.js [14.7 KB]
search.js [3.4 KB]
📁 gitbook-plugin-highlight
website.css [30.0 KB]
ebook.css [2.7 KB]
📁 gitbook-plugin-fontsettings
buttons.js [3.9 KB]
website.css [8.4 KB]
📁 gitbook-plugin-livereload
plugin.js [327.0 B]
📁 gitbook-plugin-katex
📁 fonts
KaTeX_Typewriter-Regular.eot [34.9 KB]
KaTeX_Math-Regular.eot [40.6 KB]
KaTeX_Caligraphic-Regular.eot [18.8 KB]
KaTeX_Typewriter-Regular.ttf [34.7 KB]
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KaTeX_Fraktur-Regular.woff [22.3 KB]
KaTeX_Size1-Regular.eot [13.1 KB]
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KaTeX_Caligraphic-Regular.woff2 [10.2 KB]
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KaTeX_Script-Regular.ttf [24.3 KB]
KaTeX_Typewriter-Regular.woff2 [16.9 KB]
KaTeX_Math-Italic.ttf [40.5 KB]
KaTeX_Math-Italic.woff [23.3 KB]
KaTeX_Main-Italic.eot [43.1 KB]
KaTeX_Math-BoldItalic.ttf [38.8 KB]
KaTeX_Size2-Regular.ttf [12.1 KB]
KaTeX_Fraktur-Regular.woff2 [19.4 KB]
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KaTeX_Math-Italic.eot [40.7 KB]
KaTeX_Size1-Regular.woff [6.8 KB]
KaTeX_AMS-Regular.eot [70.0 KB]
KaTeX_SansSerif-Regular.ttf [29.3 KB]
KaTeX_Script-Regular.woff2 [12.0 KB]
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KaTeX_Size3-Regular.woff [4.7 KB]
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KaTeX_SansSerif-Regular.woff2 [13.6 KB]
KaTeX_Main-Bold.ttf [59.1 KB]
KaTeX_Fraktur-Bold.ttf [35.1 KB]
KaTeX_SansSerif-Bold.ttf [33.2 KB]
KaTeX_Main-Italic.woff2 [20.5 KB]
KaTeX_Size2-Regular.woff [6.5 KB]
KaTeX_Size2-Regular.eot [12.4 KB]
KaTeX_SansSerif-Bold.woff [18.7 KB]
KaTeX_AMS-Regular.ttf [69.8 KB]
KaTeX_Caligraphic-Bold.woff2 [10.4 KB]
katex.min.css [20.5 KB]
📁 gitbook-plugin-sharing
buttons.js [2.9 KB]
📁 gitbook-plugin-expandable-chapters-small
expandable-chapters-small.css [580.0 B]
expandable-chapters-small.js [2.0 KB]
📁 fonts
📁 fontawesome
fontawesome-webfont.woff [81.8 KB]
fontawesome-webfont.eot [70.8 KB]
FontAwesome.otf [73.4 KB]
fontawesome-webfont.ttf [138.2 KB]
fontawesome-webfont.svg [247.5 KB]
📁 images
favicon.ico [4.2 KB]
apple-touch-icon-precomposed-152.png [90.6 KB]
style.css [38.3 KB]
app.js [741.5 KB]
📁 images
训练样本特正处理3.png [372.9 KB]
网络结构.png [113.6 KB]
playground两类.png [99.8 KB]
ROC曲线.png [64.1 KB]
词向量公式.png [46.7 KB]
画像业务.png [112.1 KB]
LSH官方图.png [380.6 KB]
LR简单模型特征.png [388.4 KB]
hadoop看sqoop.png [344.2 KB]
用户文章不唯一.png [338.6 KB]
用户主题词爆炸.png [229.6 KB]
流式计算与批量计算的对比.png [276.0 KB]
离线在线计算.png [116.1 KB]
中间计算结果.png [185.8 KB]
flumeevent.png [36.5 KB]
复杂两类数据分类1.png [96.4 KB]
排序逻辑.png [293.6 KB]
playground.png [34.1 KB]
实时计算图.png [478.2 KB]
推荐系统后台.png [217.6 KB]
随机投影方式.png [715.9 KB]
两类数据分类.png [110.5 KB]
处理类型个数.png [744.3 KB]
阶.png [45.8 KB]
tensorflow.png [188.9 KB]
FTRL共识.png [43.1 KB]
LSH不同的地方.png [259.9 KB]
测试样本构造.png [304.7 KB]
添加步骤.png [118.4 KB]
训练样本前期特征.png [267.6 KB]
flume第一次收集.png [106.4 KB]
表截图.png [106.3 KB]
flume参数.png [202.1 KB]
hash列.png [338.7 KB]
特征处理feature_column.png [709.8 KB]
黑马头条推荐架构图.png [164.9 KB]
黑马头条推荐流程图.png [214.7 KB]
softmax公式.png [27.9 KB]
als公式.png [8.9 KB]
add图.png [58.7 KB]
鸢尾花网络模型.png [216.9 KB]
更新环境设置.png [209.6 KB]
count结果.png [117.0 KB]
CBOW公式.png [11.6 KB]
感知机公式.png [43.0 KB]
abtest与推荐中心逻辑.png [75.3 KB]
用户关联结果2.png [160.0 KB]
目录结构1.png [19.2 KB]
复杂数据2.png [247.3 KB]
网站流量计算.png [225.1 KB]
FFM特征交叉.png [323.2 KB]
网页pagerank.png [570.7 KB]
softmax展开.png [58.3 KB]
TFAPI.png [99.2 KB]
词的无向图.png [326.3 KB]
用户画像流程作用.png [68.8 KB]
在线目录.png [14.1 KB]
textrank词性.png [480.4 KB]
模型存放目录.png [129.0 KB]
实时排序逻辑.png [102.0 KB]
tensors_flowing.gif [9.5 MB]
随机值张量.png [126.8 KB]
用户原始数据.png [96.8 KB]
排序模块.png [110.8 KB]
word2vecnn.png [119.6 KB]
minihash.png [88.1 KB]
tfidf结果.png [124.6 KB]
records.png [247.0 KB]
历史记录.png [106.1 KB]
词向量可视化效果.png [219.6 KB]
感知机.png [49.8 KB]
hadoopwv目录.png [228.8 KB]
spark启动好的.png [350.4 KB]
推荐目录.png [73.7 KB]
埋点流程.png [90.9 KB]
数据量.png [76.6 KB]
文章权重向量.png [153.4 KB]
TF动态图.gif [38.0 KB]
OP名字修改.png [29.6 KB]
sqoop导入hadoop文件数据.png [128.8 KB]
TFIDF结果2.png [111.6 KB]
类型.png [108.1 KB]
固定值张量.png [109.5 KB]
pycharm远程连接.png [178.3 KB]
LR.png [148.0 KB]
与或问题.png [38.5 KB]
鸢尾花.png [3.4 MB]
梯度下降理解.png [57.8 KB]
框架关注.png [136.2 KB]
flume外部结构.png [89.1 KB]
agent.png [103.1 KB]
hadoop启动好的.png [248.7 KB]
flume.png [110.6 KB]
PR公式.png [18.0 KB]
premadeestirmaot.png [90.7 KB]
多agent.png [250.0 KB]
基础用户画像.png [62.7 KB]
传播算法演示.png [171.7 KB]
神经元.png [247.6 KB]
交叉熵损失公式.png [22.7 KB]
📁 reco
index.html [35.4 KB]
section1.html [40.2 KB]
section2.html [37.6 KB]
📁 day05
section2.html [48.0 KB]
section1.html [44.2 KB]
index.html [35.4 KB]
index.html [36.4 KB]
search_index.json [8.5 MB]
📁 content
1.md
📁 黑马头条推荐第三天
📁 04_资料
📁 推荐算法.mindnode
📁 style.mindnodestyle
contents.xml [6.2 KB]
._metadata.plist [4.0 KB]
metadata.plist [395.0 B]
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📁 QuickLook
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📁 第三天总结.mindnode
📁 resources
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📁 QuickLook
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📁 style.mindnodestyle
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📁 02_课件
📁 最新课件到20190627
📁 day05
section1.html [43.8 KB]
section2.html [47.6 KB]
index.html [35.0 KB]
📁 reco
section1.html [39.8 KB]
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section2.html [37.2 KB]
📁 gitbook
📁 images
apple-touch-icon-precomposed-152.png [90.6 KB]
favicon.ico [4.2 KB]
📁 plugins
📁 gitbook-plugin-livereload
plugin.js [327.0 B]
📁 gitbook-plugin-search
lunr.min.js [14.7 KB]
search.css [599.0 B]
search.js [3.4 KB]
📁 gitbook-plugin-sharing
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📁 gitbook-plugin-katex
📁 fonts
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KaTeX_Main-Bold.ttf [59.1 KB]
KaTeX_Fraktur-Bold.woff [22.8 KB]
KaTeX_Size3-Regular.woff [4.7 KB]
KaTeX_Main-Bold.eot [59.3 KB]
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KaTeX_Fraktur-Regular.woff [22.3 KB]
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KaTeX_Caligraphic-Bold.woff [11.9 KB]
KaTeX_Fraktur-Regular.woff2 [19.4 KB]
KaTeX_Math-Regular.eot [40.6 KB]
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KaTeX_Typewriter-Regular.woff2 [16.9 KB]
KaTeX_Size3-Regular.ttf [8.2 KB]
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KaTeX_SansSerif-Bold.ttf [33.2 KB]
KaTeX_SansSerif-Bold.woff2 [15.6 KB]
KaTeX_AMS-Regular.woff2 [32.4 KB]
KaTeX_Script-Regular.woff [13.5 KB]
KaTeX_SansSerif-Italic.ttf [30.3 KB]
KaTeX_Main-Regular.woff2 [30.5 KB]
KaTeX_Size4-Regular.woff [6.3 KB]
KaTeX_Math-BoldItalic.eot [39.1 KB]
KaTeX_SansSerif-Italic.woff [17.7 KB]
KaTeX_Size3-Regular.eot [8.4 KB]
KaTeX_AMS-Regular.woff [39.3 KB]
KaTeX_Math-BoldItalic.woff2 [19.6 KB]
KaTeX_Size2-Regular.woff [6.5 KB]
KaTeX_Fraktur-Bold.woff2 [20.0 KB]
KaTeX_Caligraphic-Regular.woff2 [10.2 KB]
KaTeX_Size4-Regular.ttf [11.0 KB]
KaTeX_Size3-Regular.woff2 [3.8 KB]
KaTeX_SansSerif-Italic.eot [30.6 KB]
KaTeX_Caligraphic-Regular.woff [11.6 KB]
KaTeX_Fraktur-Bold.eot [35.4 KB]
KaTeX_Size1-Regular.ttf [12.9 KB]
KaTeX_Caligraphic-Regular.eot [18.8 KB]
KaTeX_Math-Italic.woff2 [20.0 KB]
KaTeX_AMS-Regular.eot [70.0 KB]
KaTeX_AMS-Regular(1).ttf [69.8 KB]
KaTeX_Caligraphic-Bold.ttf [19.1 KB]
KaTeX_Main-Regular.eot [66.6 KB]
KaTeX_Main-Italic.woff [24.3 KB]
katex.min.css [20.5 KB]
📁 gitbook-plugin-expandable-chapters-small
expandable-chapters-small.js [2.0 KB]
expandable-chapters-small.css [580.0 B]
📁 gitbook-plugin-highlight
ebook.css [2.7 KB]
website.css [30.0 KB]
📁 gitbook-plugin-fontsettings
buttons.js [3.9 KB]
website.css [8.4 KB]
📁 fonts
📁 fontawesome
fontawesome-webfont(1).woff [81.8 KB]
fontawesome-webfont.ttf [138.2 KB]
fontawesome-webfont.svg [247.5 KB]
FontAwesome.otf [73.4 KB]
fontawesome-webfont.eot [70.8 KB]
app.js [741.5 KB]
style.css [38.3 KB]
📁 day06
section3.html [59.5 KB]
section1.html [41.2 KB]
section5.html [40.7 KB]
section6.html [65.4 KB]
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📁 day04
section5.html [52.8 KB]
section2.html [47.5 KB]
section1.html [64.2 KB]
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📁 day01
section9.html [34.9 KB]
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section0.html [64.4 KB]
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section5.html [45.2 KB]
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section3.html [119.3 KB]
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📁 day02
section7.html [59.2 KB]
section8.html [63.8 KB]
section3.html [44.3 KB]
section5.html [48.8 KB]
section2.html [71.8 KB]
section1.html [50.1 KB]
section6.html [56.7 KB]
section4.html [59.4 KB]
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section9.html [34.9 KB]
section10.html [34.9 KB]
📁 day07
section1.html [65.0 KB]
section13.html [34.7 KB]
section3.html [54.8 KB]
section6.html [49.5 KB]
section12.html [34.9 KB]
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📁 day03
section1.html [43.2 KB]
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section5.html [34.9 KB]
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📁 images
训练样本特征处理4.png [334.8 KB]
复杂数据1.png [180.9 KB]
神经网络如何分类.png [126.4 KB]
随机投影方式.png [715.9 KB]
梯度下降理解.png [57.8 KB]
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识别输出概率.png [166.5 KB]
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wide&deep模型.png [289.2 KB]
tfidf结果.png [124.6 KB]
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tensors_flowing.gif [9.5 MB]
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TFAPI.png [99.2 KB]
FFM特征交叉.png [323.2 KB]
als公式.png [8.9 KB]
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sqoop导入hadoop文件数据.png [128.8 KB]
LR.png [148.0 KB]
模型存放目录.png [129.0 KB]
LSH不同的地方.png [259.9 KB]
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premadeestirmaot.png [90.7 KB]
特征处理原则.png [94.4 KB]
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LR简单模型特征.png [388.4 KB]
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als打分矩阵.png [104.7 KB]
tensorflow.png [188.9 KB]
softmax展开.png [58.3 KB]
感知机公式.png [43.0 KB]
推荐系统后台.png [217.6 KB]
OP名字修改.png [29.6 KB]
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固定值张量.png [109.5 KB]
矩阵分解.png [142.5 KB]
brand.png [239.6 KB]
损失函数图.png [126.9 KB]
黑马头条推荐流程图.png [214.7 KB]
无向图分数计算.png [310.9 KB]
catidentity.png [340.5 KB]
与或问题.png [38.5 KB]
推荐架构.png [407.9 KB]
基础用户画像.png [62.7 KB]
AB测试.png [186.3 KB]
随机值张量.png [126.8 KB]
词的无向图.png [326.3 KB]
网页pagerank.png [570.7 KB]
用户文章不唯一.png [338.6 KB]
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CBOW公式.png [11.6 KB]
hadoopwv目录.png [228.8 KB]
感知机.png [49.8 KB]
tfdataset格式.png [65.3 KB]
PR计算图.png [103.0 KB]
阶.png [45.8 KB]
PR迭代结果.png [193.7 KB]
网络优化动态图.gif [6.6 MB]
原始ALS数据.png [150.3 KB]
流量切分.png [68.2 KB]
LSH官方图.png [380.6 KB]
hbase启动好的.png [224.2 KB]
词向量解释1.png [178.9 KB]
用户原始数据.png [96.8 KB]
类别词汇表.png [347.1 KB]
传播算法演示.png [171.7 KB]
鸢尾花网络模型.png [216.9 KB]
rb概率.png [319.8 KB]
TF动态图.gif [38.0 KB]
abtest与推荐中心逻辑.png [75.3 KB]
playground.png [34.1 KB]
textrank词性.png [480.4 KB]
数据量.png [76.6 KB]
埋点流程.png [90.9 KB]
TF最新架构图.png [557.7 KB]
用户数据分类.png [231.4 KB]
框架关注.png [136.2 KB]
flume第一次收集.png [106.4 KB]
原始日志数据.png [290.8 KB]
训练样本特正处理3.png [372.9 KB]
年份分桶.png [184.0 KB]
画像业务.png [112.1 KB]
search_index.json [7.9 MB]
index.html [36.0 KB]
📁 01_视频
15_推荐结果的解析_.mp4 [48.6 MB]
02_增量更新添加_.mp4 [34.0 MB]
17_第三天总结_.mp4 [21.7 MB]
08_用户标签权重计算_.mp4 [53.1 MB]
16_召回结果的存储于总结_.mp4 [49.3 MB]
07_行为数据的更新存储_.mp4 [28.9 MB]
05_用户行为日志处理_.mp4 [89.3 MB]
06_用户行为日志处理2_.mp4 [25.4 MB]
12_召回与排序介绍_.mp4 [62.3 MB]
10_用户画像偏好标签权重计算_.mp4 [60.1 MB]
01_复习_.mp4 [63.9 MB]
13_召回表的设计与存储_.mp4 [36.7 MB]
11_用户画像定时更新开启_.mp4 [19.7 MB]
03_用户画像介绍_.mp4 [34.5 MB]
09_用户画像计算步骤_.mp4 [68.9 MB]
14_模型召回介绍与计算_.mp4 [65.0 MB]
04_头条用户画像设计_.mp4 [18.0 MB]
📁 03_代码
📁 toutiao_project
📁 scripts
import_incremental.sh [2.0 KB]
collect_click.sh [302.0 B]
📁 scheduler
main.py [966.0 B]
update(1).py [652.0 B]
update(1)(1).py [652.0 B]
📁 reco_sys
📁 offline(1)
📁 setting
logging.py [508.0 B]
📁 setting(1)
📁 offline
📁 full_cal
📁 .ipynb_checkpoints
merge_data-checkpoint.ipynb [72.0 B]
user_profile.ipynb [20.8 KB]
word2vec.ipynb [25.7 KB]
merge_data.ipynb [46.2 KB]
update_recall.ipynb [26.3 KB]
__init__.py [1.4 KB]
update_user.py [9.3 KB]
update_article.py [12.5 KB]
📁 .idea
📁 dictionaries
huxinghui.xml [88.0 B]
📁 inspectionProfiles
Project_Default.xml [790.0 B]
workspace.xml [52.9 KB]
toutiao_project.iml [603.0 B]
remote-mappings.xml [491.0 B]
encodings.xml [135.0 B]
modules.xml [282.0 B]
misc.xml [852.0 B]
deployment.xml [771.0 B]
📁 黑马头条推荐第六天
📁 04_资料
QQ20190701-111742@2x.png [742.1 KB]
._第五天课堂纪要.pdf [4.0 KB]
._QQ20190701-152531@2x.png [4.0 KB]
QQ20190701-100043@2x.png [313.2 KB]
._第六天课堂纪要.pdf [4.0 KB]
第六天课堂纪要.pdf [444.5 KB]
第五天课堂纪要.pdf [528.5 KB]
._QQ20190701-111742@2x.png [4.0 KB]
._QQ20190701-100043@2x.png [4.0 KB]
耗时整理‖免费分享 cunlove.cn.png [1.6 MB]
第六天课堂纪要.md [5.6 KB]
._第六天课堂纪要.md [4.0 KB]
📁 02_课件
📁 更新到20190701
📁 day04
section6.html [66.5 KB]
index.html [36.3 KB]
section1.html [65.5 KB]
section2.html [48.7 KB]
section5.html [54.3 KB]
section0.html [38.0 KB]
section4.html [86.0 KB]
section8.html [36.2 KB]
section7.html [36.1 KB]
section3.html [73.3 KB]
📁 day03
section4.html [44.4 KB]
section3.html [93.3 KB]
section5.html [63.8 KB]
section6.html [53.5 KB]
section9.html [36.2 KB]
index.html [36.2 KB]
section1.html [47.0 KB]
section8.html [36.1 KB]
section2.html [100.1 KB]
section7.html [103.8 KB]
📁 reco
section2.html [38.4 KB]
section1.html [41.1 KB]
index.html [36.3 KB]
📁 day01
index.html [36.3 KB]
section3.html [120.5 KB]
section9.html [36.1 KB]
section1.html [65.0 KB]
section6.html [97.8 KB]
section4.html [73.7 KB]
section8.html [36.2 KB]
section5.html [46.4 KB]
section0.html [65.6 KB]
section2.html [44.9 KB]
section7.html [47.7 KB]
📁 day07
section12.html [36.1 KB]
section4.html [49.5 KB]
section7.html [118.8 KB]
index.html [36.3 KB]
section3.html [56.0 KB]
section8.html [45.2 KB]
section13.html [36.0 KB]
section11.html [50.7 KB]
section2.html [63.1 KB]
section9.html [41.6 KB]
section5.html [67.5 KB]
section1.html [66.2 KB]
section6.html [50.8 KB]
section10.html [41.8 KB]
📁 day05
index.html [36.3 KB]
section1.html [45.0 KB]
section2.html [48.8 KB]
📁 day06
section2.html [54.9 KB]
section4.html [72.9 KB]
index.html [36.2 KB]
section3.html [60.8 KB]
section6.html [66.6 KB]
section5.html [41.9 KB]
section8.html [36.2 KB]
section1.html [42.5 KB]
section7.html [36.1 KB]
📁 gitbook
📁 plugins
📁 gitbook-plugin-fontsettings
buttons.js [3.9 KB]
website.css [8.4 KB]
📁 gitbook-plugin-search
lunr.min.js [14.7 KB]
📁 gitbook-plugin-expandable-chapters-small
expandable-chapters-small.css [580.0 B]
expandable-chapters-small.js [2.0 KB]
📁 gitbook-plugin-search
search.js [3.4 KB]
search.css [599.0 B]
📁 gitbook-plugin-sharing
buttons.js [2.9 KB]
📁 gitbook-plugin-katex
📁 fonts
KaTeX_Main-Regular.woff2 [30.5 KB]
KaTeX_SansSerif-Bold.woff [18.7 KB]
KaTeX_Size4-Regular.woff2 [5.1 KB]
KaTeX_Size1-Regular.ttf [12.9 KB]
KaTeX_Caligraphic-Regular.woff [11.6 KB]
KaTeX_Math-BoldItalic.ttf [38.8 KB]
KaTeX_Typewriter-Regular.eot [34.9 KB]
KaTeX_Math-Italic.eot [40.7 KB]
KaTeX_SansSerif-Regular.ttf [29.3 KB]
KaTeX_Math-BoldItalic.woff2 [19.6 KB]
KaTeX_Main-Bold.woff2 [28.8 KB]
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KaTeX_Main-Bold.ttf [59.1 KB]
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KaTeX_Size2-Regular.eot [12.4 KB]
KaTeX_Caligraphic-Regular.eot [18.8 KB]
KaTeX_Size3-Regular.woff [4.7 KB]
KaTeX_Fraktur-Bold.woff2 [20.0 KB]
KaTeX_Main-Italic.eot [43.1 KB]
KaTeX_Size1-Regular.woff [6.8 KB]
KaTeX_Caligraphic-Bold.woff [11.9 KB]
KaTeX_Math-BoldItalic.woff [22.6 KB]
KaTeX_Fraktur-Regular.eot [34.1 KB]
KaTeX_Script-Regular.woff [13.5 KB]
KaTeX_Math-Italic.ttf [40.5 KB]
KaTeX_SansSerif-Bold.eot [33.4 KB]
KaTeX_Size2-Regular.woff2 [5.4 KB]
KaTeX_Fraktur-Regular.ttf [33.8 KB]
KaTeX_Math-Regular.eot [40.6 KB]
KaTeX_Main-Regular.eot [66.6 KB]
KaTeX_Size2-Regular.woff [6.5 KB]
KaTeX_Size3-Regular.woff2 [3.8 KB]
KaTeX_SansSerif-Italic.eot [30.6 KB]
KaTeX_Size3-Regular.ttf [8.2 KB]
KaTeX_Size3-Regular.eot [8.4 KB]
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KaTeX_SansSerif-Regular.eot [29.5 KB]
KaTeX_Script-Regular.eot [24.5 KB]
KaTeX_Script-Regular.ttf [24.3 KB]
KaTeX_AMS-Regular.eot [70.0 KB]
KaTeX_SansSerif-Regular.woff [16.4 KB]
KaTeX_Fraktur-Bold.ttf [35.1 KB]
KaTeX_SansSerif-Regular.woff2 [13.6 KB]
KaTeX_Math-Regular.ttf [40.3 KB]
KaTeX_AMS-Regular.woff2 [32.4 KB]
KaTeX_SansSerif-Bold.ttf [33.2 KB]
KaTeX_Main-Regular.woff [36.7 KB]
KaTeX_Size2-Regular.ttf [12.1 KB]
KaTeX_Script-Regular.woff2 [12.0 KB]
KaTeX_SansSerif-Italic.woff [17.7 KB]
KaTeX_Main-Italic.ttf [42.9 KB]
KaTeX_Caligraphic-Bold.ttf [19.1 KB]
KaTeX_Size4-Regular.ttf [11.0 KB]
KaTeX_AMS-Regular.ttf [69.8 KB]
KaTeX_Math-Regular.woff2 [19.9 KB]
KaTeX_Main-Italic.woff [24.3 KB]
KaTeX_Typewriter-Regular.ttf [34.7 KB]
KaTeX_Caligraphic-Bold.eot [19.4 KB]
KaTeX_Main-Regular.ttf [66.4 KB]
KaTeX_Main-Italic.woff2 [20.5 KB]
KaTeX_Size1-Regular.woff2 [5.7 KB]
KaTeX_Typewriter-Regular.woff2 [16.9 KB]
KaTeX_SansSerif-Italic.ttf [30.3 KB]
KaTeX_Math-Italic.woff2 [20.0 KB]
KaTeX_Math-BoldItalic.eot [39.1 KB]
KaTeX_Typewriter-Regular.woff [20.2 KB]
KaTeX_Size4-Regular.eot [11.3 KB]
KaTeX_SansSerif-Bold.woff2 [15.6 KB]
KaTeX_Fraktur-Regular.woff2 [19.4 KB]
KaTeX_Fraktur-Bold.eot [35.4 KB]
KaTeX_Main-Bold.woff [34.6 KB]
KaTeX_Size1-Regular.eot [13.1 KB]
KaTeX_Size4-Regular.woff [6.3 KB]
KaTeX_Caligraphic-Bold.woff2 [10.4 KB]
KaTeX_Math-Italic.woff [23.3 KB]
KaTeX_SansSerif-Italic.woff2 [14.8 KB]
KaTeX_Fraktur-Regular.woff [22.3 KB]
KaTeX_Math-Regular.woff [23.2 KB]
katex.min.css [20.5 KB]
📁 gitbook-plugin-livereload
plugin.js [327.0 B]
📁 gitbook-plugin-highlight
website.css [30.0 KB]
ebook.css [2.7 KB]
📁 fonts
📁 fontawesome
fontawesome-webfont.svg [247.5 KB]
fontawesome-webfont.ttf [138.2 KB]
fontawesome-webfont.eot [70.8 KB]
fontawesome-webfont.woff [81.8 KB]
FontAwesome.otf [73.4 KB]
📁 images
apple-touch-icon-precomposed-152.png [90.6 KB]
favicon.ico [4.2 KB]
app.js [741.5 KB]
style.css [38.3 KB]
📁 images
hash列.png [338.7 KB]
阶.png [45.8 KB]
PR计算图.png [103.0 KB]
查看倾斜.png [292.4 KB]
网站流量计算.png [225.1 KB]
历史日志信息导入.png [130.9 KB]
黑马头条宣传.png [761.2 KB]
历史记录.png [106.1 KB]
softmax公式.png [27.9 KB]
PR迭代结果.png [193.7 KB]
hadoopwv目录.png [228.8 KB]
数据倾斜方案1.png [717.5 KB]
词向量公式.png [46.7 KB]
用户画像流程作用.png [68.8 KB]
textrank公式.png [24.7 KB]
框架关注.png [136.2 KB]
单层感知机.png [119.8 KB]
hbase启动好的.png [224.2 KB]
关联推荐结果.png [233.7 KB]
catidentity.png [340.5 KB]
LSH官方图.png [380.6 KB]
用户关联结果2.png [160.0 KB]
传播算法演示.png [171.7 KB]
用户主题词爆炸.png [229.6 KB]
关联结果1.png [326.2 KB]
模型存放目录.png [129.0 KB]
minihash2.png [86.8 KB]
添加步骤.png [118.4 KB]
无向图分数计算.png [310.9 KB]
在线目录.png [14.1 KB]
单agent多sink.png [245.4 KB]
softmax回归.png [112.2 KB]
records.png [247.0 KB]
LR简单模型特征.png [388.4 KB]
spark启动好的.png [350.4 KB]
表截图.png [106.3 KB]
完整工程目录.png [62.3 KB]
词的无向图.png [326.3 KB]
tfdataset格式.png [65.3 KB]
基础用户画像.png [62.7 KB]
flume参数.png [202.1 KB]
推荐目录.png [51.4 KB]
鸢尾花.png [3.4 MB]
处理类型个数.png [744.3 KB]
kafka.png [36.8 KB]
实时在线flume设置.png [45.5 KB]
hadoop启动好的.png [248.7 KB]
PC.png [311.3 KB]
系统耦合高.png [117.7 KB]
合并用户文章.png [200.1 KB]
交叉熵损失公式.png [22.7 KB]
loadbalance.png [463.9 KB]
交叉损失理解.png [121.1 KB]
黑马头条推荐架构图.png [164.9 KB]
固定值张量.png [109.5 KB]
网络优化动态图.gif [6.6 MB]
推荐架构.png [407.9 KB]
复杂数据2.png [247.3 KB]
实时排序逻辑.png [102.0 KB]
随机值张量.png [126.8 KB]
感知机公式.png [43.0 KB]
复杂两类数据分类.png [114.0 KB]
count结果.png [117.0 KB]
梯度下降理解.png [57.8 KB]
spark运行原理过程.png [1012.4 KB]
实时计算图.png [478.2 KB]
中间计算结果.png [185.8 KB]
replica.png [153.4 KB]
als公式.png [8.9 KB]
矩阵分解.png [142.5 KB]
rb概率.png [319.8 KB]
数据流图.png [164.2 KB]
类型变换.png [68.6 KB]
召回读取服务.png [33.2 KB]
单agent.png [128.1 KB]
tensors_flowing.gif [9.5 MB]
目录结构1.png [19.2 KB]
profucer写数据过程.png [221.7 KB]
Textrank原理.png [56.2 KB]
LSH不同的地方.png [259.9 KB]
生产者设计.png [215.4 KB]
mappred.png [907.0 KB]
flume外部结构.png [89.1 KB]
排序模块.png [110.8 KB]
网页pagerank.png [570.7 KB]
FTRL共识.png [43.1 KB]
流式计算.png [226.9 KB]
类别词汇表.png [347.1 KB]
测试样本构造.png [304.7 KB]
CBOW公式.png [11.6 KB]
TF最新架构图.png [557.7 KB]
softmax展开.png [58.3 KB]
ROC曲线.png [64.1 KB]
词向量可视化效果.png [219.6 KB]
多agent.png [250.0 KB]
TFAPI.png [99.2 KB]
index关系结构.png [293.7 KB]
AB测试.png [186.3 KB]
召回模块.png [87.2 KB]
TF构建流程.png [508.1 KB]
📁 day02
section5.html [51.3 KB]
section3.html [45.5 KB]
section10.html [36.1 KB]
section7.html [60.4 KB]
section2.html [73.1 KB]
index.html [36.4 KB]
section6.html [57.8 KB]
section4.html [60.6 KB]
section8.html [65.0 KB]
section1.html [51.3 KB]
section9.html [36.1 KB]
index.html [37.2 KB]
search_index.json [9.3 MB]
📁 03_代码
📁 toutiao_project
📁 scheduler
main(1).py [1.3 KB]
update.py [1.1 KB]
📁 .idea
modules.xml [282.0 B]
📁 .idea
encodings.xml [135.0 B]
📁 .idea
📁 inspectionProfiles
Project_Default.xml [790.0 B]
📁 dictionaries
huxinghui.xml [88.0 B]
misc.xml [852.0 B]
workspace.xml [53.7 KB]
toutiao_project.iml [603.0 B]
remote-mappings.xml [491.0 B]
📁 reco_sys
📁 online
__init__.py [1.1 KB]
online_update.py [5.7 KB]
📁 server
__init__.py [434.0 B]
recall_service.py [4.0 KB]
utils.py [4.0 KB]
reco_centor.py [11.3 KB]
📁 abtest
routing.py [6.0 KB]
grpc_test.py [1.7 KB]
user_reco_pb2.py [11.8 KB]
user_reco.proto [738.0 B]
user_reco_pb2_grpc.py [2.1 KB]
📁 setting
default.py [2.1 KB]
logging.py [1.2 KB]
📁 offline
📁 full_cal(1)
📁 full_cal
📁 .ipynb_checkpoints
merge_data-checkpoint.ipynb [72.0 B]
lr_sort.ipynb [170.1 KB]
update_recall.ipynb [30.5 KB]
user_profile.ipynb [20.8 KB]
merge_data.ipynb [46.2 KB]
word2vec.ipynb [25.7 KB]
update_article(1).py [12.5 KB]
__init__(1).py [2.4 KB]
update_user(1).py [9.3 KB]
hbaset.py [536.0 B]
update_recall(1).py [9.5 KB]
update_user.py [9.3 KB]
update_feature.py [4.7 KB]
update_recall.py [9.5 KB]
update_article.py [12.5 KB]
hbaset(1).py [536.0 B]
__init__.py [2.4 KB]
update_feature(1).py [4.7 KB]
📁 scripts
collect_click.sh [302.0 B]
import_incremental.sh [2.0 KB]
start_kafka.sh [498.0 B]
📁 .idea
deployment.xml [771.0 B]
📁 01_视频
01_复习_.mp4 [45.1 MB]
07_推荐中心调用效果总结_.mp4 [31.9 MB]
06_推荐中心刷新逻辑实现_.mp4 [193.5 MB]
04_abtest介绍_.mp4 [31.0 MB]
03_grpc接口后台对接实现_.mp4 [88.8 MB]
09_推荐中心加入召回读取过滤存储结果_.mp4 [156.0 MB]
05_abtest流量切分实现_.mp4 [46.6 MB]
08_召回读取接口构建_.mp4 [75.1 MB]
02_实时推荐流程逻辑_.mp4 [74.3 MB]
📁 黑马头条推荐第十天
📁 04_资料
📁 项目总结.mindnode
📁 resources
6C6A4723-904C-4ACC-BAA4-C72C8191690C.png [414.6 KB]
📁 style.mindnodestyle
contents.xml [6.2 KB]
metadata.plist [395.0 B]
📁 QuickLook
Preview.jpg [145.6 KB]
contents.xml [99.1 KB]
viewState.plist [179.0 B]
QQ20190707-121655@2x.png [581.4 KB]
QQ20190707-102224@2x.png [182.2 KB]
面试简历指导.pdf [3.8 MB]
面试简历指导.md [15.6 KB]
QQ20190707-101851@2x.png [424.5 KB]
第十天课堂纪要.pdf [9.5 KB]
QQ20190707-121244@2x.png [420.7 KB]
QQ20190707-100954@2x.png [491.0 KB]
耗时整理‖免费分享 cunlove.cn.png [512.7 KB]
QQ20190707-102949@2x.png [528.3 KB]
第十天课堂纪要.md [7.9 KB]
📁 03_代码
📁 toutiao_project
📁 scripts
collect_click.sh [302.0 B]
import_incremental.sh [2.0 KB]
start_kafka.sh [498.0 B]
📁 .idea
📁 inspectionProfiles
Project_Default.xml [790.0 B]
📁 dictionaries
huxinghui.xml [88.0 B]
encodings.xml [135.0 B]
deployment.xml [771.0 B]
misc.xml [852.0 B]
modules.xml [282.0 B]
workspace.xml [57.7 KB]
toutiao_project.iml [603.0 B]
remote-mappings.xml [491.0 B]
📁 scheduler
update.py [1.1 KB]
main.py [1.3 KB]
📁 reco_sys
📁 setting
logging.py [1.2 KB]
default.py [2.4 KB]
📁 abtest
user_reco_pb2.py [11.8 KB]
routing.py [6.0 KB]
user_reco.proto [738.0 B]
grpc_test.py [1.7 KB]
user_reco_pb2_grpc.py [2.1 KB]
📁 server
📁 models
📁 tmp
📁 summary
📁 linear
…（层级过深，已停止）
events.out.tfevents.1561765617.hadoop-master [650.0 B]
events.out.tfevents.1561766113.hadoop-master [650.0 B]
events.out.tfevents.1561764557.hadoop-master [690.0 B]
📁 ckpt
📁 wide_and_deep
…（层级过深，已停止）
📁 linear
…（层级过深，已停止）
📁 data
adult.data [3.4 MB]
adult.test [1.7 MB]
📁 serving_model
📁 wdl
📁 1561997467
…（层级过深，已停止）
demo.py [5.6 KB]
wide_deep.py [4.2 KB]
census_predict.py [10.6 KB]
nn_text_classification.py [2.2 KB]
ctr_train_20190706.tfrecords [3.5 MB]
census_example.py [3.7 KB]
train_ctr_20190605.tfrecords [3.5 MB]
heima_ftrl.py [4.0 KB]
__init__.py [940.0 B]
utils.py [4.0 KB]
reco_centor.py [12.2 KB]
redis_cache.py [3.9 KB]
sort_service.py [9.2 KB]
recall_service.py [4.0 KB]
📁 online
__init__.py [1.1 KB]
online_update.py [5.7 KB]
📁 offline
📁 full_cal
📁 .ipynb_checkpoints
lr_sort-checkpoint.ipynb [72.0 B]
word2vec-checkpoint.ipynb [72.0 B]
online_sort-checkpoint.ipynb [72.0 B]
user_profile-checkpoint.ipynb [72.0 B]
update_recall-checkpoint.ipynb [26.5 KB]
merge_data-checkpoint.ipynb [72.0 B]
user_profile.ipynb [20.8 KB]
online_sort.ipynb [9.0 KB]
word2vec.ipynb [25.7 KB]
lr_sort.ipynb [189.9 KB]
update_recall.ipynb [30.5 KB]
merge_data.ipynb [46.2 KB]
update_article.py [12.5 KB]
update_user.py [9.3 KB]
hbaset.py [536.0 B]
update_feature.py [4.7 KB]
__init__.py [2.4 KB]
text_class.py [2.3 KB]
update_recall.py [9.5 KB]
📁 RSPaper
1301.3781.pdf [223.4 KB]
bengio03a.pdf [136.8 KB]
百面机器学习.pdf [25.2 MB]
在线最优化求解(Online Optimization)-冯扬.pdf [961.1 KB]
hlww-2018124152810.pdf [1.2 MB]
paragraph_vector.pdf [286.1 KB]
📁 02_课件
📁 01_视频
08_模型导出_.mp4 [58.3 MB]
05_FTRL模型训练对比_.mp4 [46.3 MB]
01_复习_.mp4 [31.2 MB]
07_widedeep模型训练_.mp4 [46.1 MB]
11_项目总结1_.mp4 [80.9 MB]
10_grpc模型服务调用预测_.mp4 [79.8 MB]
09_Serving模型服务部署_.mp4 [28.0 MB]
03_FTRL原理介绍_.mp4 [41.3 MB]
06_深度学习CTR演化图_.mp4 [48.4 MB]
04_FTRL数据输入_.mp4 [98.0 MB]
02_FM与FTRL介绍_.mp4 [45.9 MB]
13_面试简历指导_.mp4 [96.1 MB]
12_项目总结2_.mp4 [28.2 MB]
黑马头条推荐系统完整课件V3.0.zip [65.2 MB]
📁 黑马头条推荐第一天
📁 01_视频
10_pR与textrank原理_.mp4 [46.7 MB]
09_TFIDF计算_.mp4 [71.4 MB]
11_textrank计算_.mp4 [19.6 MB]
12_总结_.mp4 [12.4 MB]
07_文章画像介绍与构建_.mp4 [104.2 MB]
08_文章数据合并_.mp4 [79.1 MB]
06_离线计算_.mp4 [62.4 MB]
03_sqoop迁移_.mp4 [121.4 MB]
01_推荐系统介绍_.mp4 [34.4 MB]
04_sqoop迁移与定时脚本_.mp4 [45.0 MB]
05_定时脚本添加_.mp4 [113.7 MB]
02_环境介绍_.mp4 [45.7 MB]
📁 04_资料
📁 第一天总结.mindnode
📁 style.mindnodestyle
metadata.plist [395.0 B]
contents.xml [6.2 KB]
._metadata.plist [4.0 KB]
._contents(1).xml [4.0 KB]
📁 QuickLook
._Preview.jpg [4.0 KB]
Preview.jpg [132.4 KB]
._contents.xml [4.0 KB]
._viewState.plist [4.0 KB]
._resources [4.0 KB]
._QuickLook [4.0 KB]
viewState.plist [178.0 B]
contents.xml [19.4 KB]
._style.mindnodestyle [4.0 KB]
._黑马头条推荐分布式&单机版大数据环境使用教程.md [4.0 KB]
第一天课堂纪要.md [12.2 KB]
._第一天课堂纪要.md [4.0 KB]
黑马头条推荐分布式&单机版大数据环境使用教程.md [7.0 KB]
耗时整理‖免费分享 cunlove.cn.png [328.9 KB]
._黑马头条推荐分布式&单机版大数据环境使用教程.pdf [4.0 KB]
黑马头条推荐分布式&单机版大数据环境使用教程.pdf [689.6 KB]
._QQ20190624-094741@2x.png [4.0 KB]
._第一天总结.mindnode [4.0 KB]
📁 03_代码
📁 toutiao_project
📁 scripts
collect_click.sh [302.0 B]
import_incremental.sh [2.0 KB]
📁 .idea
📁 dictionaries
huxinghui.xml [88.0 B]
📁 inspectionProfiles
Project_Default.xml [790.0 B]
misc.xml [852.0 B]
encodings.xml [135.0 B]
toutiao_project.iml [603.0 B]
modules.xml [282.0 B]
remote-mappings.xml [491.0 B]
workspace.xml [51.3 KB]
deployment.xml [771.0 B]
📁 reco_sys
📁 offline(1)
📁 offline
📁 full_cal
📁 .ipynb_checkpoints
merge_data-checkpoint.ipynb [72.0 B]
merge_data.ipynb [31.4 KB]
__init__.py [1.4 KB]
📁 02_课件
📁 _book
📁 reco
section2.html [37.2 KB]
index.html [35.0 KB]
section1.html [39.8 KB]
📁 day07
section11.html [49.4 KB]
section1.html [65.0 KB]
section13.html [34.7 KB]
section4.html [48.3 KB]
section10.html [40.6 KB]
section9.html [40.3 KB]
section7.html [117.5 KB]
section5.html [66.2 KB]
section6.html [49.5 KB]
section2.html [61.9 KB]
section8.html [44.0 KB]
section12.html [34.9 KB]
section3.html [54.8 KB]
index.html [35.0 KB]
📁 day06
section3.html [59.5 KB]
section6.html [65.4 KB]
section7.html [34.9 KB]
section8.html [34.9 KB]
section5.html [40.7 KB]
section2.html [53.7 KB]
index.html [35.0 KB]
section4.html [71.6 KB]
section1.html [41.2 KB]
📁 day04
section3.html [76.3 KB]
section1.html [64.2 KB]
section6.html [65.2 KB]
section0.html [36.7 KB]
section5.html [52.8 KB]
section4.html [83.8 KB]
section8.html [34.9 KB]
section2.html [47.5 KB]
index.html [35.0 KB]
section7.html [34.9 KB]
📁 gitbook
📁 fonts
📁 fontawesome
fontawesome-webfont.woff [81.8 KB]
fontawesome-webfont.eot [70.8 KB]
fontawesome-webfont.ttf [138.2 KB]
FontAwesome.otf [73.4 KB]
fontawesome-webfont.svg [247.5 KB]
📁 plugins
📁 gitbook-plugin-search
search.js [3.4 KB]
search.css [599.0 B]
lunr.min.js [14.7 KB]
📁 gitbook-plugin-sharing
buttons.js [2.9 KB]
📁 gitbook-plugin-highlight
website.css [30.0 KB]
ebook.css [2.7 KB]
📁 gitbook-plugin-katex
📁 fonts
KaTeX_Fraktur-Regular.ttf [33.8 KB]
KaTeX_Script-Regular.eot [24.5 KB]
KaTeX_Main-Italic.eot [43.1 KB]
KaTeX_Main-Bold.woff [34.6 KB]
KaTeX_Caligraphic-Bold.woff2 [10.4 KB]
KaTeX_Size4-Regular.eot [11.3 KB]
KaTeX_Script-Regular.woff [13.5 KB]
KaTeX_Size3-Regular.ttf [8.2 KB]
KaTeX_AMS-Regular.woff [39.3 KB]
KaTeX_Math-Italic.eot [40.7 KB]
KaTeX_SansSerif-Bold.woff [18.7 KB]
KaTeX_Size4-Regular.woff2 [5.1 KB]
KaTeX_Caligraphic-Regular.ttf [18.5 KB]
KaTeX_Math-Italic.woff [23.3 KB]
KaTeX_Size2-Regular.woff [6.5 KB]
KaTeX_SansSerif-Regular.ttf [29.3 KB]
KaTeX_Caligraphic-Bold.ttf [19.1 KB]
KaTeX_SansSerif-Italic.ttf [30.3 KB]
KaTeX_Size2-Regular.eot [12.4 KB]
KaTeX_Caligraphic-Regular.woff [11.6 KB]
KaTeX_Typewriter-Regular.ttf [34.7 KB]
KaTeX_Typewriter-Regular.woff [20.2 KB]
KaTeX_Size1-Regular.woff2 [5.7 KB]
KaTeX_Size3-Regular.woff2 [3.8 KB]
KaTeX_Size2-Regular.ttf [12.1 KB]
KaTeX_SansSerif-Bold.ttf [33.2 KB]
KaTeX_Fraktur-Bold.woff2 [20.0 KB]
KaTeX_Main-Bold.woff2 [28.8 KB]
KaTeX_Math-Italic.ttf [40.5 KB]
KaTeX_AMS-Regular.eot [70.0 KB]
KaTeX_Main-Bold.ttf [59.1 KB]
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KaTeX_Fraktur-Regular.woff2 [19.4 KB]
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KaTeX_Caligraphic-Regular.woff2 [10.2 KB]
KaTeX_Typewriter-Regular.eot [34.9 KB]
KaTeX_Caligraphic-Bold.eot [19.4 KB]
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KaTeX_Main-Italic.woff2 [20.5 KB]
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KaTeX_Main-Bold.eot [59.3 KB]
KaTeX_Caligraphic-Bold.woff [11.9 KB]
KaTeX_Size3-Regular.eot [8.4 KB]
KaTeX_SansSerif-Italic.woff [17.7 KB]
KaTeX_Script-Regular.woff2 [12.0 KB]
KaTeX_SansSerif-Bold.woff2 [15.6 KB]
KaTeX_Math-Italic.woff2 [20.0 KB]
KaTeX_SansSerif-Bold.eot [33.4 KB]
KaTeX_Main-Italic.woff [24.3 KB]
KaTeX_Fraktur-Bold.woff [22.8 KB]
KaTeX_SansSerif-Italic.woff2 [14.8 KB]
KaTeX_Size4-Regular.ttf [11.0 KB]
KaTeX_Math-BoldItalic.woff [22.6 KB]
KaTeX_Typewriter-Regular.woff2 [16.9 KB]
KaTeX_Main-Regular.eot [66.6 KB]
KaTeX_Main-Regular.woff [36.7 KB]
KaTeX_Main-Italic.ttf [42.9 KB]
KaTeX_Size3-Regular.woff [4.7 KB]
KaTeX_Fraktur-Bold.ttf [35.1 KB]
KaTeX_Size1-Regular.ttf [12.9 KB]
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katex.min.css [20.5 KB]
📁 gitbook-plugin-fontsettings
website.css [8.4 KB]
buttons.js [3.9 KB]
📁 gitbook-plugin-livereload
plugin.js [327.0 B]
📁 gitbook-plugin-expandable-chapters-small
expandable-chapters-small.js [2.0 KB]
expandable-chapters-small.css [580.0 B]
📁 images
apple-touch-icon-precomposed-152.png [90.6 KB]
favicon.ico [4.2 KB]
app.js [741.5 KB]
style.css [38.3 KB]
📁 day05
section2.html [47.6 KB]
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index.html [35.0 KB]
📁 day03
section3.html [52.2 KB]
section1.html [43.2 KB]
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index.html [35.0 KB]
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📁 images
softmax公式.png [27.9 KB]
直线方程.png [28.0 KB]
FTRL共识.png [43.1 KB]
数据量.png [76.6 KB]
计算关键词中间结果.png [120.9 KB]
离线样本构造.png [258.5 KB]
黑马头条宣传.png [761.2 KB]
复杂两类数据分类1.png [96.4 KB]
推荐结果.png [115.4 KB]
rb概率.png [319.8 KB]
框架关注.png [136.2 KB]
与或问题.png [38.5 KB]
原始日志数据.png [290.8 KB]
textrank公式.png [24.7 KB]
单层感知机.png [119.8 KB]
交叉熵损失公式.png [22.7 KB]
召回排序1.png [125.0 KB]
PR迭代结果.png [193.7 KB]
目录结构1.png [19.2 KB]
处理类型个数.png [744.3 KB]
TFIDF结果2.png [111.6 KB]
用户原始数据.png [96.8 KB]
网络结构.png [113.6 KB]
TF动态图.gif [38.0 KB]
推荐架构.png [407.9 KB]
黑马头条推荐流程图.png [214.7 KB]
als公式.png [8.9 KB]
CBOW公式.png [11.6 KB]
黑马头条推荐架构图.png [164.9 KB]
运行的APP.png [357.1 KB]
hash列.png [338.7 KB]
召回读取服务.png [41.4 KB]
流量切分.png [68.2 KB]
brand.png [239.6 KB]
排序逻辑.png [293.6 KB]
als打分矩阵.png [104.7 KB]
serving图.png [139.2 KB]
类型.png [108.1 KB]
TF最新架构图.png [557.7 KB]
用户主题词爆炸.png [229.6 KB]
词向量解释1.png [178.9 KB]
用户画像流程作用.png [21.4 KB]
PR公式.png [18.0 KB]
推荐目录.png [73.7 KB]
records.png [247.0 KB]
网络优化动态图.gif [6.6 MB]
文章权重向量.png [153.4 KB]
添加步骤.png [118.4 KB]
词的无向图.png [296.8 KB]
AB测试.png [186.3 KB]
spark启动好的.png [350.4 KB]
minihash2.png [86.8 KB]
完整工程目录.png [62.3 KB]
梯度下降理解.png [57.8 KB]
tfdataset格式.png [65.3 KB]
wide&deep模型.png [289.2 KB]
训练样本前期特征.png [267.6 KB]
类别词汇表.png [347.1 KB]
阶.png [45.8 KB]
特征处理feature_column.png [709.8 KB]
识别输出概率.png [166.5 KB]
softmax展开.png [58.3 KB]
原始ALS数据.png [150.3 KB]
hadoop启动好的.png [248.7 KB]
固定值张量.png [109.5 KB]
ROC曲线.png [64.1 KB]
sqoop导入hadoop文件数据.png [128.8 KB]
感知机公式.png [43.0 KB]
年份分桶.png [184.0 KB]
LR简单模型特征.png [388.4 KB]
PR计算图.png [103.0 KB]
用户关联结果2.png [160.0 KB]
Tensorboard.png [35.1 KB]
矩阵分解.png [142.5 KB]
premadeestirmaot.png [90.7 KB]
合并用户文章.png [200.1 KB]
随机值张量.png [126.8 KB]
flume第一次收集.png [106.4 KB]
更新环境设置.png [209.6 KB]
tensorflow.png [188.9 KB]
类型变换.png [68.6 KB]
中间计算结果.png [185.8 KB]
训练样本特正处理3.png [372.9 KB]
playground.png [34.1 KB]
损失函数图.png [126.9 KB]
历史日志信息导入.png [130.9 KB]
测试样本构造.png [304.7 KB]
LSH不同的地方.png [259.9 KB]
OP名字修改.png [29.6 KB]
关联推荐结果.png [233.7 KB]
画像业务.png [112.1 KB]
召回排序结构.png [172.9 KB]
LR.png [148.0 KB]
复杂数据1.png [180.9 KB]
神经网络如何分类.png [126.4 KB]
传播算法演示.png [171.7 KB]
词向量公式.png [46.7 KB]
textrank词性.png [480.4 KB]
softmax回归.png [112.2 KB]
add图.png [58.7 KB]
📁 day01
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📁 day02
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index.html [35.1 KB]
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search_index.json [7.3 MB]
index.html [36.0 KB]
📁 黑马头条推荐第五天
📁 03_代码
📁 toutiao_project
📁 scripts
collect_click.sh [302.0 B]
import_incremental.sh [2.0 KB]
start_kafka.sh [498.0 B]
📁 reco_sys
📁 online
__init__.py [1.1 KB]
online_update.py [5.7 KB]
📁 setting
logging.py [847.0 B]
default.py [506.0 B]
📁 offline
📁 full_cal
📁 .ipynb_checkpoints
merge_data-checkpoint.ipynb [72.0 B]
update_recall.ipynb [30.5 KB]
lr_sort.ipynb [170.1 KB]
word2vec.ipynb [25.7 KB]
merge_data.ipynb [46.2 KB]
user_profile.ipynb [20.8 KB]
update_recall.py [9.5 KB]
hbaset.py [536.0 B]
__init__.py [2.4 KB]
update_article.py [12.5 KB]
update_feature.py [4.7 KB]
update_user.py [9.3 KB]
📁 .idea
📁 inspectionProfiles
Project_Default.xml [790.0 B]
📁 dictionaries
huxinghui.xml [88.0 B]
modules.xml [282.0 B]
misc.xml [852.0 B]
encodings.xml [135.0 B]
workspace.xml [55.7 KB]
remote-mappings.xml [491.0 B]
toutiao_project.iml [603.0 B]
deployment.xml [771.0 B]
📁 scheduler
main.py [1.3 KB]
update.py [1.1 KB]
📁 04_资料
QQ20190630-111934@2x.png [446.2 KB]
._第五天课堂纪要.md [4.0 KB]
._QQ20190630-111934@2x.png [4.0 KB]
._第五天课堂纪要.pdf [4.0 KB]
第五天课堂纪要.md [12.2 KB]
QQ20190630-123306@2x.png [948.5 KB]
第五天课堂纪要.pdf [18.6 KB]
QQ20190630-111652@2x.png [324.3 KB]
._QQ20190630-123306@2x.png [4.0 KB]
._QQ20190630-153602@2x.png [4.0 KB]
耗时整理‖免费分享 cunlove.cn.png [4.0 KB]
QQ20190630-153602@2x.png [509.2 KB]
📁 02_课件
📁 更新到20190630
📁 day03
section6.html [53.5 KB]
section9.html [36.2 KB]
section2.html [100.1 KB]
section5.html [63.8 KB]
section1.html [47.0 KB]
index.html [36.2 KB]
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section7.html [103.8 KB]
section3.html [93.3 KB]
section4.html [44.4 KB]
📁 day01
section4.html [73.7 KB]
section5.html [46.4 KB]
index.html [36.3 KB]
section1.html [65.0 KB]
section7.html [47.7 KB]
section9.html [36.1 KB]
section0.html [65.6 KB]
section2.html [44.9 KB]
section8.html [36.2 KB]
section6.html [97.8 KB]
section3.html [120.5 KB]
📁 images
年份分桶.png [184.0 KB]
加入MQ.png [134.8 KB]
replica.png [153.4 KB]
复杂数据2.png [247.3 KB]
感知机.png [49.8 KB]
count结果.png [117.0 KB]
数据倾斜.png [1.0 MB]
agent.png [103.1 KB]
用户文章不唯一.png [338.6 KB]
损失函数图.png [126.9 KB]
模型存放目录.png [129.0 KB]
FFM特征交叉.png [323.2 KB]
两类数据分类.png [110.5 KB]
处理类型个数.png [744.3 KB]
textrank公式.png [24.7 KB]
中间计算结果.png [185.8 KB]
推荐系统业务架构.png [328.5 KB]
hadoopwv目录.png [228.8 KB]
测试样本构造.png [304.7 KB]
无向图分数计算.png [310.9 KB]
profucer写数据过程.png [221.7 KB]
基础用户画像.png [62.7 KB]
离线样本构造.png [258.5 KB]
网页pagerank.png [570.7 KB]
tensorflow.png [188.9 KB]
flume第一次收集.png [106.4 KB]
计算关键词中间结果.png [120.9 KB]
矩阵分解.png [142.5 KB]
实时计算图.png [478.2 KB]
Tensorboard.png [35.1 KB]
训练样本前期特征.png [267.6 KB]
rb概率.png [319.8 KB]
神经元.png [247.6 KB]
鸢尾花.png [3.4 MB]
playground两类.png [99.8 KB]
特征处理原则.png [94.4 KB]
loadbalance.png [463.9 KB]
排序逻辑.png [293.6 KB]
softmax展开.png [58.3 KB]
消费者设计.png [275.3 KB]
类型.png [108.1 KB]
传播算法演示.png [171.7 KB]
网络优化动态图.gif [6.6 MB]
spark启动好的.png [350.4 KB]
流量切分.png [68.2 KB]
词向量公式.png [46.7 KB]
minihash2.png [86.8 KB]
flume实战.png [137.8 KB]
词向量可视化效果.png [219.6 KB]
流式计算与批量计算的对比.png [276.0 KB]
brand.png [239.6 KB]
词向量解释1.png [178.9 KB]
随机投影方式.png [715.9 KB]
spark运行原理过程.png [1012.4 KB]
倾斜解决方案2.png [500.0 KB]
TF最新架构图.png [557.7 KB]
单agent.png [128.1 KB]
多agent.png [250.0 KB]
flume外部结构.png [89.1 KB]
TF动态图.gif [38.0 KB]
与或问题.png [38.5 KB]
运行的APP.png [357.1 KB]
用户关联结果2.png [160.0 KB]
CBOW公式.png [11.6 KB]
区别.png [162.8 KB]
复杂两类数据分类.png [114.0 KB]
用户主题词爆炸.png [229.6 KB]
交叉熵损失公式.png [22.7 KB]
LSH不同的地方.png [259.9 KB]
用户数据分类.png [231.4 KB]
textrank词性.png [480.4 KB]
数据量.png [76.6 KB]
wide&deep模型.png [289.2 KB]
历史日志信息导入.png [130.9 KB]
数据流图.png [164.2 KB]
感知机公式.png [43.0 KB]
records.png [247.0 KB]
mappred.png [907.0 KB]
复杂数据1.png [180.9 KB]
Textrank原理.png [56.2 KB]
TF构建流程.png [508.1 KB]
minihash.png [88.1 KB]
召回读取服务.png [41.4 KB]
更新环境设置.png [209.6 KB]
实时排序逻辑.png [102.0 KB]
词的无向图.png [326.3 KB]
abtest与推荐中心逻辑.png [75.3 KB]
离线在线计算.png [116.1 KB]
推荐系统后台.png [217.6 KB]
历史记录.png [106.1 KB]
神经网络如何分类.png [126.4 KB]
复杂两类数据分类1.png [96.4 KB]
groupbykey.png [838.2 KB]
playground.png [34.1 KB]
flume参数1.png [403.0 KB]
flumeevent.png [36.5 KB]
特征处理feature_column.png [709.8 KB]
在线目录.png [14.1 KB]
tfdataset格式.png [65.3 KB]
表截图.png [106.3 KB]
📁 gitbook
📁 fonts
📁 fontawesome
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fontawesome-webfont.svg [247.5 KB]
fontawesome-webfont.woff [81.8 KB]
fontawesome-webfont.ttf [138.2 KB]
fontawesome-webfont.eot [70.8 KB]
📁 images
apple-touch-icon-precomposed-152.png [90.6 KB]
favicon.ico [4.2 KB]
📁 plugins
📁 gitbook-plugin-fontsettings
buttons.js [3.9 KB]
website.css [8.4 KB]
📁 gitbook-plugin-katex
📁 fonts
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KaTeX_Caligraphic-Regular.ttf [18.5 KB]
KaTeX_Math-Italic.eot [40.7 KB]
KaTeX_Size1-Regular.eot [13.1 KB]
KaTeX_Typewriter-Regular.ttf [34.7 KB]
KaTeX_Main-Regular.ttf [66.4 KB]
KaTeX_Fraktur-Regular.woff [22.3 KB]
KaTeX_Main-Bold.woff2 [28.8 KB]
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KaTeX_Fraktur-Regular.woff2 [19.4 KB]
KaTeX_AMS-Regular.eot [70.0 KB]
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KaTeX_Math-Regular.woff2 [19.9 KB]
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KaTeX_Math-BoldItalic.ttf [38.8 KB]
KaTeX_Fraktur-Bold.ttf [35.1 KB]
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KaTeX_Main-Regular.woff2 [30.5 KB]
KaTeX_Typewriter-Regular.eot [34.9 KB]
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KaTeX_Math-Regular.ttf [40.3 KB]
KaTeX_SansSerif-Regular.woff [16.4 KB]
KaTeX_SansSerif-Bold.woff2 [15.6 KB]
KaTeX_Math-BoldItalic.woff [22.6 KB]
KaTeX_Size4-Regular.woff [6.3 KB]
KaTeX_SansSerif-Regular.ttf [29.3 KB]
KaTeX_Script-Regular.eot [24.5 KB]
KaTeX_Main-Bold.woff [34.6 KB]
KaTeX_Main-Regular.eot [66.6 KB]
KaTeX_Math-Regular.eot [40.6 KB]
KaTeX_Size2-Regular.eot [12.4 KB]
KaTeX_Main-Italic.woff [24.3 KB]
KaTeX_Size3-Regular.woff2 [3.8 KB]
KaTeX_Main-Regular.woff [36.7 KB]
KaTeX_AMS-Regular.ttf [69.8 KB]
KaTeX_Math-BoldItalic.eot [39.1 KB]
KaTeX_AMS-Regular.woff2 [32.4 KB]
KaTeX_SansSerif-Italic.ttf [30.3 KB]
KaTeX_Typewriter-Regular.woff [20.2 KB]
KaTeX_Main-Italic.eot [43.1 KB]
KaTeX_Script-Regular.ttf [24.3 KB]
KaTeX_Math-Italic.woff2 [20.0 KB]
KaTeX_Caligraphic-Bold.eot [19.4 KB]
KaTeX_Math-Italic.ttf [40.5 KB]
KaTeX_Main-Bold.eot [59.3 KB]
KaTeX_Caligraphic-Regular.woff [11.6 KB]
KaTeX_SansSerif-Bold.woff [18.7 KB]
KaTeX_Math-Regular.woff [23.2 KB]
KaTeX_Math-BoldItalic.woff2 [19.6 KB]
KaTeX_SansSerif-Italic.woff2 [14.8 KB]
KaTeX_Size4-Regular.woff2 [5.1 KB]
KaTeX_Script-Regular.woff2 [12.0 KB]
KaTeX_Math-Italic.woff [23.3 KB]
KaTeX_Size2-Regular.woff2 [5.4 KB]
KaTeX_Fraktur-Regular.ttf [33.8 KB]
KaTeX_Main-Italic.woff2 [20.5 KB]
KaTeX_SansSerif-Bold.ttf [33.2 KB]
KaTeX_Caligraphic-Bold.woff [11.9 KB]
katex.min.css [20.5 KB]
📁 gitbook-plugin-search
search.css [599.0 B]
search.js [3.4 KB]
lunr.min.js [14.7 KB]
📁 gitbook-plugin-expandable-chapters-small
expandable-chapters-small.js [2.0 KB]
expandable-chapters-small(1).css [580.0 B]
📁 gitbook-plugin-sharing
buttons.js [2.9 KB]
📁 gitbook-plugin-highlight
ebook.css [2.7 KB]
website.css [30.0 KB]
📁 gitbook-plugin-livereload
plugin.js [327.0 B]
style.css [38.3 KB]
app.js [741.5 KB]
📁 day05
section1.html [45.0 KB]
index.html [36.3 KB]
section2.html [48.8 KB]
📁 day02
section9.html [36.1 KB]
section10.html [36.1 KB]
section2.html [73.1 KB]
section4.html [60.6 KB]
section6.html [57.8 KB]
index.html [36.4 KB]
section3.html [45.5 KB]
section5.html [51.3 KB]
section8.html [65.0 KB]
section7.html [60.4 KB]
section1.html [51.3 KB]
📁 reco
section1.html [41.1 KB]
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📁 day06
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📁 day07
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_book.zip [58.2 MB]
search_index.json [9.3 MB]
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📁 01_视频
14_在线更新程序定时更新_.mp4 [8.4 MB]
02_flume介绍_.mp4 [87.0 MB]
08_kafka案例_.mp4 [58.8 MB]
13_新文章召回代码_.mp4 [16.5 MB]
04_flume收集案例2_.mp4 [74.9 MB]
10_Streamin在线内容召回实现_.mp4 [40.4 MB]
12_新文章热门文章召回_.mp4 [51.8 MB]
07_kafka的生产者与消费者_.mp4 [45.2 MB]
01_复习_.mp4 [45.1 MB]
06_kafka介绍与存储原理_.mp4 [148.1 MB]
03_flume收集案例1_.mp4 [29.3 MB]
09_黑马推荐实时flume与kafka对接_.mp4 [54.3 MB]
05_flume实战_.mp4 [51.2 MB]
11_在线内容召回结果实现_.mp4 [68.0 MB]
15_spark优化了解_.mp4 [103.9 MB]
📁 黑马头条推荐系统完整课件V3.0
📁 day02
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📁 gitbook
📁 images
apple-touch-icon-precomposed-152.png [90.6 KB]
favicon.ico [4.2 KB]
📁 plugins
📁 gitbook-plugin-sharing
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KaTeX_Fraktur-Regular.ttf [33.8 KB]
KaTeX_Script-Regular.eot [24.5 KB]
katex.min.css [20.5 KB]
📁 gitbook-plugin-livereload
plugin.js [327.0 B]
📁 gitbook-plugin-highlight
website(1).css [30.0 KB]
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📁 gitbook-plugin-search
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search.css [599.0 B]
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📁 gitbook-plugin-expandable-chapters-small
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📁 day03
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📁 day07
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📁 day08
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📁 day06
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📁 images
更新环境设置.png [209.6 KB]
年份分桶.png [184.0 KB]
计算关键词中间结果.png [120.9 KB]
实时在线flume设置.png [45.5 KB]
PR迭代结果.png [193.7 KB]
神经元.png [79.1 KB]
历史日志信息导入.png [130.9 KB]
流式计算与批量计算的对比.png [276.0 KB]
测试样本构造.png [304.7 KB]
复杂数据1.png [72.9 KB]
LSH官方图.png [380.6 KB]
word2vecnn.png [119.6 KB]
深度学习CTR演化关系图.png [214.6 KB]
rb概率.png [319.8 KB]
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识别输出概率.png [166.5 KB]
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投影公式.png [9.2 KB]
sqoop导入hadoop文件数据.png [128.8 KB]
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埋点流程.png [90.9 KB]
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TF动态图.gif [38.0 KB]
gbdt排序.png [195.6 KB]
运行的APP.png [357.1 KB]
感知机公式.png [20.1 KB]
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relu.png [23.3 KB]
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梯度下降理解.png [57.8 KB]
pycharm远程连接.png [178.3 KB]
hadoopwv目录.png [228.8 KB]
FTRL共识.png [43.1 KB]
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损失函数图.png [126.9 KB]
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系统耦合高.png [117.7 KB]
premadeestirmaot.png [90.7 KB]
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tensorflow.png [188.9 KB]
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playground两类.png [104.1 KB]
LSH不同的地方.png [259.9 KB]
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用户画像流程作用.png [68.8 KB]
TFAPI.png [99.2 KB]
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第二部分求导.png [170.1 KB]
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cbow-skip.png [90.5 KB]
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神经语言概率案例.png [137.4 KB]
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📁 day04
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📁 day05
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📁 day01
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📁 黑马头条推荐第七天
📁 02_课件
📁 更新到20190703
📁 day02
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📁 day05
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📁 fonts
📁 fontawesome
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search.js [3.4 KB]
lunr.min.js [14.7 KB]
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📁 day03
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📁 reco
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📁 day04
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📁 day01
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📁 images
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Tensorboard.png [35.1 KB]
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流式计算与批量计算的对比.png [276.0 KB]
合并用户文章.png [200.1 KB]
spark启动好的.png [350.4 KB]
网站流量计算.png [225.1 KB]
单agent多sink.png [245.4 KB]
softmax展开.png [58.3 KB]
LSH不同的地方.png [259.9 KB]
Textrank原理.png [56.2 KB]
词的无向图.png [326.3 KB]
网络优化动态图.gif [6.6 MB]
add图.png [58.7 KB]
tensorflowgithub.png [164.5 KB]
更新环境设置.png [209.6 KB]
词向量解释1.png [178.9 KB]
tfdataset格式.png [65.3 KB]
用户主题词爆炸.png [229.6 KB]
复杂两类数据分类1.png [96.4 KB]
hbase启动好的.png [224.2 KB]
单层感知机.png [119.8 KB]
数据流图.png [164.2 KB]
黑马头条推荐流程图.png [214.7 KB]
FTRL共识.png [43.1 KB]
PR公式.png [18.0 KB]
replica.png [153.4 KB]
神经元.png [247.6 KB]
特征处理原则.png [94.4 KB]
数据倾斜时间.png [518.3 KB]
用户关联结果2.png [160.0 KB]
flume参数.png [202.1 KB]
minihash2.png [86.8 KB]
sqoop导入hadoop文件数据.png [128.8 KB]
TF动态图.gif [38.0 KB]
推荐架构.png [407.9 KB]
类别词汇表.png [347.1 KB]
softmax公式.png [27.9 KB]
传播算法演示.png [171.7 KB]
实时计算图.png [478.2 KB]
两类数据分类.png [110.5 KB]
鸢尾花网络模型.png [216.9 KB]
profucer写数据过程.png [221.7 KB]
用户数据分类.png [231.4 KB]
埋点流程.png [90.9 KB]
搜索兴趣度.png [182.6 KB]
数据量.png [76.6 KB]
brand.png [239.6 KB]
textrank公式.png [24.7 KB]
PR计算图.png [103.0 KB]
训练样本特征处理4.png [334.8 KB]
关联结果1.png [326.2 KB]
flumeevent.png [36.5 KB]
召回模块.png [87.2 KB]
阶.png [45.8 KB]
groupbykey.png [838.2 KB]
minihash.png [88.1 KB]
感知机公式.png [43.0 KB]
TFAPI.png [99.2 KB]
LR.png [148.0 KB]
kafka.png [36.8 KB]
类型变换.png [68.6 KB]
用户原始数据.png [96.8 KB]
复杂数据1.png [180.9 KB]
年份分桶.png [184.0 KB]
排序模块.png [110.8 KB]
hadoop看sqoop.png [344.2 KB]
flume第一次收集.png [106.4 KB]
数据倾斜.png [1.0 MB]
文章权重向量.png [153.4 KB]
playground.png [34.1 KB]
wide&deep模型.png [289.2 KB]
tensors_flowing.gif [9.5 MB]
与或问题.png [38.5 KB]
复杂两类数据分类.png [114.0 KB]
textrank词性.png [480.4 KB]
TF构建流程.png [508.1 KB]
训练样本特正处理3.png [372.9 KB]
CBOW公式.png [11.6 KB]
历史日志信息导入.png [130.9 KB]
识别输出概率.png [166.5 KB]
多agent.png [250.0 KB]
单agent.png [128.1 KB]
生产者设计.png [215.4 KB]
softmax回归.png [112.2 KB]
flume.png [110.6 KB]
LR简单模型特征.png [388.4 KB]
消费者设计.png [275.3 KB]
catidentity.png [340.5 KB]
复杂数据2.png [247.3 KB]
PR迭代结果.png [193.7 KB]
playground两类.png [99.8 KB]
处理类型个数.png [744.3 KB]
倾斜解决方案2.png [500.0 KB]
计算关键词中间结果.png [120.9 KB]
画像业务.png [112.1 KB]
pycharm远程连接.png [178.3 KB]
abtest与推荐中心逻辑.png [75.3 KB]
投影公式.png [9.2 KB]
网络结构.png [113.6 KB]
📁 day07
section6.html [50.8 KB]
section10.html [41.8 KB]
section5.html [67.5 KB]
section1.html [66.2 KB]
section7.html [118.8 KB]
section2.html [63.1 KB]
section13.html [36.0 KB]
index.html [36.3 KB]
section3.html [56.0 KB]
section4.html [49.5 KB]
section11.html [50.7 KB]
section8.html [45.2 KB]
section12.html [36.1 KB]
section9.html [41.6 KB]
📁 day06
section8.html [36.2 KB]
index.html [36.2 KB]
section2.html [54.9 KB]
section7.html [36.1 KB]
section6.html [66.6 KB]
section4.html [73.3 KB]
section5.html [41.9 KB]
section1.html [42.5 KB]
section3.html [60.8 KB]
index.html [37.2 KB]
search_index.json [10.6 MB]
_book.zip [58.2 MB]
📁 04_资料
._第七天课堂纪要.pdf [4.0 KB]
耗时整理‖免费分享 cunlove.cn.png [234.1 KB]
QQ20190703-165144@2x.png [493.2 KB]
第七天课堂纪要.pdf [144.8 KB]
第七天课堂纪要.md [6.4 KB]
._QQ20190703-175158@2x.png [4.0 KB]
._第七天课堂纪要.md [4.0 KB]
._QQ20190703-165144@2x.png [4.0 KB]
📁 01_视频
04_LR模型排序测试_.mp4 [144.7 MB]
01_复习_.mp4 [34.9 MB]
08_TF的图与节点OP特点_.mp4 [80.0 MB]
10_张量与变量_.mp4 [68.7 MB]
11_案例：线性回归实现与训练_.mp4 [71.1 MB]
02_推荐缓存实现_.mp4 [99.8 MB]
03_推荐缓存测试_.mp4 [29.1 MB]
07_TF数据流图_.mp4 [34.0 MB]
06_推荐系统与深度学习介绍_.mp4 [87.9 MB]
05_模型排序问题解决以及添加推荐中心_.mp4 [65.5 MB]
09_会话_.mp4 [39.1 MB]
📁 03_代码
📁 toutiao_project
📁 .idea
📁 inspectionProfiles
Project_Default.xml [790.0 B]
📁 dictionaries
huxinghui.xml [88.0 B]
encodings.xml [135.0 B]
toutiao_project.iml [603.0 B]
modules.xml [282.0 B]
misc.xml [852.0 B]
workspace.xml [56.3 KB]
remote-mappings.xml [491.0 B]
deployment.xml [771.0 B]
📁 scripts
collect_click.sh [302.0 B]
import_incremental.sh [2.0 KB]
start_kafka.sh [498.0 B]
📁 reco_sys
📁 offline
📁 models
📁 tmp
📁 summary
events.out.tfevents.1561764557.hadoop-master [690.0 B]
demo.py [4.5 KB]
📁 full_cal
📁 .ipynb_checkpoints
merge_data-checkpoint.ipynb [72.0 B]
lr_sort.ipynb [170.1 KB]
user_profile.ipynb [20.8 KB]
word2vec.ipynb [25.7 KB]
online_sort.ipynb [9.0 KB]
merge_data.ipynb [46.2 KB]
update_recall.ipynb [30.5 KB]
hbaset.py [536.0 B]
update_recall.py [9.5 KB]
update_feature.py [4.7 KB]
update_user.py [9.3 KB]
update_article.py [12.5 KB]
__init__.py [2.4 KB]
📁 abtest
user_reco_pb2_grpc.py [2.1 KB]
routing.py [6.0 KB]
grpc_test.py [1.7 KB]
user_reco(1).proto [738.0 B]
user_reco_pb2.py [11.8 KB]
📁 online
online_update.py [5.7 KB]
__init__.py [1.1 KB]
📁 setting
logging.py [1.2 KB]
default.py [2.4 KB]
📁 server
recall_service.py [4.0 KB]
redis_cache.py [3.9 KB]
reco_centor.py [12.2 KB]
__init__.py [925.0 B]
utils.py [4.0 KB]
sort_service.py [3.1 KB]
📁 scheduler
update.py [1.1 KB]
main.py [1.3 KB]
📁 toutiao_project
📁 reco_sys
📁 server
utils.py [4.0 KB]
recall_service.py [4.0 KB]
redis_cache.py [3.9 KB]
sort_service.py [3.1 KB]
__init__.py [925.0 B]
reco_centor.py [12.2 KB]
📁 setting
logging.py [1.2 KB]
default.py [2.4 KB]
📁 offline
📁 full_cal
📁 .ipynb_checkpoints
merge_data-checkpoint.ipynb [72.0 B]
update_recall.ipynb [30.5 KB]
word2vec.ipynb [25.7 KB]
lr_sort.ipynb [170.1 KB]
merge_data.ipynb [46.2 KB]
online_sort.ipynb [9.0 KB]
user_profile.ipynb [20.8 KB]
update_article.py [12.5 KB]
update_recall.py [9.5 KB]
__init__.py [2.4 KB]
update_user.py [9.3 KB]
update_feature.py [4.7 KB]
hbaset.py [536.0 B]
📁 online
online_update.py [5.7 KB]
__init__.py [1.1 KB]
📁 abtest
routing.py [6.0 KB]
grpc_test.py [1.7 KB]
user_reco_pb2_grpc.py [2.1 KB]
user_reco.proto [738.0 B]
user_reco_pb2.py [11.8 KB]
📁 scripts
start_kafka.sh [498.0 B]
import_incremental.sh [2.0 KB]
collect_click.sh [302.0 B]
📁 scheduler
update.py [1.1 KB]
main.py [1.3 KB]
📁 .idea
📁 dictionaries
huxinghui.xml [88.0 B]
📁 inspectionProfiles
Project_Default.xml [790.0 B]
remote-mappings.xml [491.0 B]
workspace.xml [55.4 KB]
modules.xml [282.0 B]
toutiao_project.iml [603.0 B]
encodings(1).xml [135.0 B]
deployment.xml [771.0 B]
misc.xml [852.0 B]
📁 data
adult.test [1.7 MB]
adult.data [3.4 MB]
黑马头条推荐分布式&单机版大数据环境使用教程.pdf [689.6 KB]
黑马头条推荐系统完整课件V3.0.zip [65.2 MB]
demo.py [5.6 KB]
归档.zip [622.1 KB]
📁 01_数据分析概要
01_数据科学内容概述_.mp4 [30.4 MB]
12_数据指标_业务指标_.mp4 [22.3 MB]
02_数据分析岗位介绍_.mp4 [18.0 MB]
04_数据分析技能要求_.mp4 [24.3 MB]
11_数据指标_行为指标_.mp4 [21.9 MB]
10_数据指标_留存指标_.mp4 [53.0 MB]
03_业务的概念_.mp4 [42.1 MB]
07_数据指标_行为指标业务指标_.mp4 [18.2 MB]
08_数据指标_日活月活_.mp4 [21.2 MB]
05_数据指标概念_.mp4 [24.7 MB]
09_数据指标_日活月活2_.mp4 [13.0 MB]
13_数据指标_业务指标定义_.mp4 [79.0 MB]
06_数据指标_用户数据_.mp4 [43.8 MB]
📁 05_数据处理
19_appstore数据分析_案例总结_.mp4 [42.6 MB]
08_数据处理_离散化案例_.mp4 [33.2 MB]
20_优衣库案例总结_.mp4 [46.4 MB]
13_链家数据处理案例_.mp4 [44.2 MB]
01_内容回顾_.mp4 [16.3 MB]
10_数据处理_样本分布不均衡_.mp4 [28.7 MB]
21_内容回顾_.mp4 [11.7 MB]
12_数据处理总结_.mp4 [14.4 MB]
14_链家数据处理案例2_.mp4 [60.6 MB]
17_appstore数据分析_价格单变量分析_.mp4 [36.8 MB]
02_智能运营内容说明_.mp4 [20.0 MB]
15_appstore数据分析_.mp4 [11.3 MB]
04_数据处理_异常值重复值_.mp4 [27.7 MB]
16_appstore数据分析_基本情况分析_.mp4 [19.6 MB]
07_数据处理_离散化_.mp4 [28.7 MB]
03_数据处理_缺失值_.mp4 [34.8 MB]
11_数据处理_数据采样衡_.mp4 [46.5 MB]
06_数据处理_数值型数据的归一化标准化_.mp4 [32.4 MB]
09_数据处理_分类特征数据处理_.mp4 [25.8 MB]
05_数据处理_异常值重复值案例_.mp4 [35.5 MB]
18_appstore数据分析_数据可视化_.mp4 [27.9 MB]
📁 09_评分卡
16_lightgbm简介_.mp4 [26.1 MB]
06_逻辑回归评分卡模型评估报告_.mp4 [39.0 MB]
18_lightgbm跨时间交叉验证代码实现_.mp4 [55.9 MB]
15_集成学习总结_.mp4 [13.6 MB]
14_XGBoost常用调参_.mp4 [34.0 MB]
09_评分卡流程回顾_.mp4 [11.3 MB]
04_逻辑回归评分卡模型代码实现_.mp4 [33.0 MB]
10_GBDT原理简介_.mp4 [27.0 MB]
19_lightgbm评分卡实现_.mp4 [10.6 MB]
03_评分卡模型评价_ROC图的绘制_.mp4 [8.4 MB]
01_内容回顾_.mp4 [45.6 MB]
12_XGBoost的API练习_印第安糖尿病案例_.mp4 [37.3 MB]
13_XGBoost的early_stopping参数_.mp4 [19.7 MB]
02_评分卡模型评价_KS值_.mp4 [69.8 MB]
05_逻辑回归评分卡lgbm特征选择_.mp4 [40.5 MB]
07_逻辑回归评分卡模型评估报告2_.mp4 [19.8 MB]
21_内容回顾_.mp4 [77.5 MB]
11_XGBoost和GBDT区别说明_.mp4 [23.5 MB]
17_lightgbm跨时间交叉验证思路分析_.mp4 [37.3 MB]
08_逻辑回归评分卡计算信用分和评级_.mp4 [42.2 MB]
20_问题说明_.mp4 [18.1 MB]
📁 06_聚类分析
02_聚类分析介绍_.mp4 [44.4 MB]
07_airbnb案例代码_.mp4 [53.2 MB]
04_聚类分析案例2_.mp4 [32.1 MB]
12_线性回归案例内容回顾_.mp4 [31.9 MB]
14_线性回归套路总结_.mp4 [51.7 MB]
03_聚类分析结果展示_.mp4 [26.4 MB]
15_社交电商线性回归分析总结_.mp4 [7.5 MB]
11_内容总结_.mp4 [113.6 MB]
10_回归分析案例分析_.mp4 [24.7 MB]
09_回归分析总结_.mp4 [50.8 MB]
08_共享单车案例总结_.mp4 [44.1 MB]
05_聚类分析_年龄收入分群_.mp4 [26.4 MB]
06_airbnb案例_.mp4 [18.1 MB]
13_线性回归数据的基本处理_.mp4 [21.8 MB]
📁 推荐系统项目
📁 day05-day10
📁 day10
📁 pics
📁 a
ml14.png [98.7 KB]
ml28.png [39.5 KB]
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env2.PNG [23.8 KB]
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ml18.png [180.4 KB]
1540347389671.png [52.7 KB]
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kafka_15.png [56.2 KB]
kafka_8.png [386.8 KB]
env4.png [191.5 KB]
ml20.png [40.7 KB]
ml06.png [166.4 KB]
ml17.png [87.2 KB]
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s3.PNG [86.2 KB]
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ml07.png [74.2 KB]
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s11.PNG [232.2 KB]
ss8.PNG [296.5 KB]
ml13.png [25.2 KB]
ss7.png [87.9 KB]
1540350260244.png [223.5 KB]
kafka_2.png [22.7 KB]
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ml09.png [76.4 KB]
env5.png [178.3 KB]
ss16.png [85.1 KB]
ss6.png [163.3 KB]
ml05.png [83.5 KB]
s4.PNG [286.5 KB]
ml1.0.md [299.0 B]
s1.4.md [9.0 KB]
s1.0.md [339.0 B]
ml1.1.md [4.4 KB]
s1.4 - 副本.md [7.8 KB]
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s1.2.md [791.0 B]
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s.md [115.0 B]
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📁 day07
📁 pics
kafka_16.png [51.2 KB]
kafka_15.png [56.2 KB]
1540350260244.png [223.5 KB]
kafka_11.png [78.6 KB]
kafka_7.png [393.8 KB]
f4.png [22.9 KB]
kafka_17.png [129.5 KB]
kafka_3.png [83.6 KB]
f1.png [447.0 KB]
k3.PNG [65.8 KB]
1540347422756.png [102.2 KB]
1540350201715.png [78.7 KB]
k2.PNG [22.7 KB]
1540347389671.png [52.7 KB]
k5.PNG [58.4 KB]
kafka_6.png [60.6 KB]
1540350245310.png [223.5 KB]
kafka_4.png [60.6 KB]
kafka_2.png [22.7 KB]
1540347375394.png [52.7 KB]
kafka_10.png [238.6 KB]
f3.png [36.9 KB]
kafka_12.png [147.0 KB]
kafka_8.png [386.8 KB]
f2.png [114.3 KB]
kafka_5.png [253.0 KB]
kafka_14.png [91.6 KB]
kafka_13.png [222.3 KB]
k1.PNG [19.1 KB]
k4.PNG [18.2 KB]
宽依赖和窄依赖.png [250.5 KB]
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kafka_9.png [57.1 KB]
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k1.0.md [454.0 B]
f1.6.md [6.7 KB]
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f.md [300.0 B]
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f1.1.md [2.5 KB]
k.md [160.0 B]
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k1.4.md [1.5 KB]
f1.3.md [301.0 B]
📁 day05
📁 img
📁 hdfs_read_write
k.jpg [53.1 KB]
g.jpg [155.1 KB]
i.jpg [157.6 KB]
e.jpg [156.9 KB]
a.jpg [135.6 KB]
c.jpg [135.7 KB]
h.jpg [156.2 KB]
d.jpg [137.8 KB]
j.jpg [156.4 KB]
b.jpg [138.3 KB]
hadoop-yarn.jpg [34.5 KB]
yarn4.png [70.9 KB]
image-大数据应用2.png [1.3 MB]
hadoop-yarn3.png [96.4 KB]
mp5.png [863.2 KB]
hadoop-hdfs1.png [29.3 KB]
image-yarn2.png [652.6 KB]
hdfs_arc.png [55.9 KB]
mp4.png [461.0 KB]
image-mapreduce2.png [668.1 KB]
image-mapreduce3.png [1.1 MB]
hadoop-hdfsarchitecture.png [39.6 KB]
image-mapreduce1.png [327.3 KB]
mp1.png [991.2 KB]
image-MapReduce5.png [334.6 KB]
image-MapReduce4.png [335.6 KB]
image-mapreduce.png [524.6 KB]
yarn_architecture.gif [32.3 KB]
hadoop-生态.png [396.0 KB]
image-大数据行业应用.png [526.8 KB]
mr_result.png [38.1 KB]
image-yarn.png [656.7 KB]
image-bigdata01.png [546.4 KB]
mp6.png [916.5 KB]
image-大数据应用3.png [1008.5 KB]
mp3.png [666.8 KB]
image-hadoop1.png [433.1 KB]
ha1.0.md [150.0 B]
ha1.4.md [950.0 B]
ha2.2.md [522.0 B]
ha2.6.md [2.1 KB]
ha1.5.md [256.0 B]
ha2.1.md [412.0 B]
ha2.3.md [1.9 KB]
ha.md [115.0 B]
ha2.4.md [1.9 KB]
ha1.1.md [2.4 KB]
ha2.5.md [4.5 KB]
ha1.2.md [1.3 KB]
ha2.0.md [212.0 B]
ha2.7.md [268.0 B]
ha1.3.md [324.0 B]
📁 day09
📁 pics
1540350201715.png [78.7 KB]
kafka_5.png [253.0 KB]
1540350674304.png [21.2 KB]
kafka_15.png [56.2 KB]
kafka_9.png [57.1 KB]
s11.PNG [232.2 KB]
s14.PNG [128.0 KB]
s5.PNG [143.6 KB]
kafka_2.png [22.7 KB]
1540350245310.png [223.5 KB]
s13.PNG [297.4 KB]
kafka_8.png [386.8 KB]
1540349692086.png [47.4 KB]
kafka_14.png [91.6 KB]
s7.PNG [339.4 KB]
kafka_6.png [60.6 KB]
1540347422756.png [102.2 KB]
kafka_7.png [393.8 KB]
s12.PNG [305.8 KB]
s4.PNG [286.5 KB]
1540349678122.png [37.2 KB]
kafka_13.png [222.3 KB]
s8.PNG [203.5 KB]
1540347389671.png [52.7 KB]
宽依赖和窄依赖.png [250.5 KB]
1540350260244.png [223.5 KB]
kafka_4.png [60.6 KB]
kafka_12.png [147.0 KB]
1540347254561.png [32.7 KB]
kafka_3.png [83.6 KB]
kafka_16.png [51.2 KB]
s9.PNG [292.5 KB]
s6.PNG [102.5 KB]
kafka_10.png [238.6 KB]
kafka_11.png [78.6 KB]
kafka_17.png [129.5 KB]
s3.PNG [86.2 KB]
s1.PNG [19.0 KB]
s10.PNG [79.2 KB]
1540347375394.png [52.7 KB]
s2.PNG [16.6 KB]
s1.5.md [7.2 KB]
s1.2.md [7.8 KB]
s.md [84.0 B]
s1.1.md [2.4 KB]
s1.3.md [6.5 KB]
s1.4.md [20.8 KB]
s1.0.md [186.0 B]
📁 day08
📁 pics
kafka_14.png [91.6 KB]
宽依赖和窄依赖.png [250.5 KB]
kafka_12.png [147.0 KB]
kafka_2.png [22.7 KB]
1540347254561.png [32.7 KB]
kafka_15.png [56.2 KB]
kafka_16.png [51.2 KB]
s3.PNG [86.2 KB]
spark3.PNG [90.6 KB]
1540350260244.png [223.5 KB]
1540350201715.png [78.7 KB]
1540350245310.png [223.5 KB]
1540349692086.png [47.4 KB]
s2.PNG [16.6 KB]
kafka_10.png [238.6 KB]
1540349678122.png [37.2 KB]
s8.PNG [203.5 KB]
kafka_7.png [393.8 KB]
kafka_17.png [129.5 KB]
spark2.PNG [12.0 KB]
spark1.PNG [15.4 KB]
kafka_4.png [60.6 KB]
kafka_5.png [253.0 KB]
1540347389671.png [52.7 KB]
kafka_6.png [60.6 KB]
s4.PNG [286.5 KB]
kafka_3.png [83.6 KB]
s5.PNG [143.6 KB]
s1.PNG [19.0 KB]
kafka_13.png [222.3 KB]
1540347422756.png [102.2 KB]
1540347375394.png [52.7 KB]
kafka_11.png [78.6 KB]
kafka_8.png [386.8 KB]
s7.PNG [339.4 KB]
1540350674304.png [21.2 KB]
s6.PNG [102.5 KB]
kafka_9.png [57.1 KB]
📁 资料
user.txt [150.0 B]
20090121000132.394251.http.format [1.9 MB]
ip.txt [13.7 MB]
access.log [2.9 MB]
s1.2.md [1.4 KB]
s1.1.md [8.4 KB]
s.md [71.0 B]
s1.6.md [4.8 KB]
s1.3.md [655.0 B]
s1.4.md [4.7 KB]
s1.5.md [2.7 KB]
s1.0.md [242.0 B]
📁 _book
📁 day08
📁 pics
宽依赖和窄依赖.png [250.5 KB]
kafka_5.png [253.0 KB]
kafka_9.png [57.1 KB]
kafka_15.png [56.2 KB]
1540349678122.png [37.2 KB]
1540350201715.png [78.7 KB]
s3.PNG [86.2 KB]
kafka_17.png [129.5 KB]
kafka_11.png [78.6 KB]
kafka_16.png [51.2 KB]
kafka_6.png [60.6 KB]
s5.PNG [143.6 KB]
kafka_7.png [393.8 KB]
s6.PNG [102.5 KB]
1540347375394.png [52.7 KB]
kafka_12.png [147.0 KB]
kafka_10.png [238.6 KB]
s2.PNG [16.6 KB]
kafka_13.png [222.3 KB]
1540350245310.png [223.5 KB]
kafka_3.png [83.6 KB]
spark2.PNG [12.0 KB]
kafka_8.png [386.8 KB]
s4.PNG [286.5 KB]
1540350674304.png [21.2 KB]
spark3.PNG [90.6 KB]
kafka_14.png [91.6 KB]
1540350260244.png [223.5 KB]
s7.PNG [339.4 KB]
s8.PNG [203.5 KB]
1540349692086.png [47.4 KB]
kafka_2.png [22.7 KB]
1540347422756.png [102.2 KB]
kafka_4.png [60.6 KB]
1540347389671.png [52.7 KB]
1540347254561.png [32.7 KB]
s1.PNG [19.0 KB]
spark1.PNG [15.4 KB]
📁 资料
ip.txt [13.7 MB]
20090121000132.394251.http.format [1.9 MB]
access.log [2.9 MB]
user.txt [150.0 B]
s1.0.html [30.4 KB]
s1.3.md [655.0 B]
s1.3.html [30.5 KB]
s1.2.md [1.4 KB]
s1.5.html [36.7 KB]
s.html [30.0 KB]
s1.2.html [33.0 KB]
s1.6.md [4.8 KB]
s1.1.html [48.7 KB]
s1.6.html [42.1 KB]
s1.4.html [41.2 KB]
s1.1.md [8.4 KB]
s1.0.md [242.0 B]
s.md [71.0 B]
s1.5.md [2.7 KB]
s1.4.md [4.7 KB]
📁 gitbook
📁 gitbook-plugin-search
lunr.min.js [14.7 KB]
search.js [6.2 KB]
search-engine.js [1.2 KB]
search.css [974.0 B]
📁 images
favicon.ico [4.2 KB]
apple-touch-icon-precomposed-152.png [4.7 KB]
📁 gitbook-plugin-highlight
ebook.css [2.8 KB]
website.css [30.7 KB]
📁 gitbook-plugin-fontsettings
fontsettings.js [6.3 KB]
website.css [8.4 KB]
📁 gitbook-plugin-livereload
plugin.js [327.0 B]
📁 fonts
📁 fontawesome
fontawesome-webfont.ttf [149.2 KB]
fontawesome-webfont.woff2 [70.2 KB]
fontawesome-webfont.eot [74.7 KB]
fontawesome-webfont.svg [382.4 KB]
fontawesome-webfont.woff [88.3 KB]
FontAwesome.otf [122.1 KB]
📁 gitbook-plugin-sharing
buttons.js [2.8 KB]
📁 gitbook-plugin-lunr
lunr.min.js [14.7 KB]
search-lunr.js [1.6 KB]
theme.js [110.6 KB]
style.css [51.5 KB]
gitbook.js [102.9 KB]
📁 day10
📁 pics
ml36.png [187.9 KB]
1540347254561.png [32.7 KB]
ss15.png [157.0 KB]
1540347422756.png [102.2 KB]
ss3.PNG [376.6 KB]
s1.PNG [19.0 KB]
kafka_10.png [238.6 KB]
ml35.png [11.8 KB]
1540347389671.png [52.7 KB]
kafka_16.png [51.2 KB]
ml03.png [97.6 KB]
ss13.png [166.8 KB]
1540350201715.png [78.7 KB]
1540350674304.png [21.2 KB]
1540350260244.png [223.5 KB]
ml04.png [103.7 KB]
ml20.png [40.7 KB]
s5.PNG [143.6 KB]
ml01.png [66.3 KB]
env3.PNG [20.6 KB]
ml11.png [174.8 KB]
s11.PNG [232.2 KB]
ss17.png [72.8 KB]
ml37.png [45.5 KB]
ss1.png [328.2 KB]
kafka_13.png [222.3 KB]
1540347375394.png [52.7 KB]
ss16.png [85.1 KB]
ss4.PNG [165.9 KB]
ml30.png [260.2 KB]
ml05.png [83.5 KB]
ss14.png [101.1 KB]
ss6.png [163.3 KB]
kafka_12.png [147.0 KB]
ss11.png [367.8 KB]
env4.png [191.5 KB]
s3.PNG [86.2 KB]
ss18.PNG [398.8 KB]
ss8.PNG [296.5 KB]
ml16.png [28.7 KB]
ml31.png [95.6 KB]
ml10.png [215.3 KB]
ml26.png [137.7 KB]
ss10.png [52.1 KB]
ml32.png [16.7 KB]
ml23.png [10.1 KB]
kafka_15.png [56.2 KB]
kafka_9.png [57.1 KB]
ml19.png [20.7 KB]
宽依赖和窄依赖.png [250.5 KB]
ss12.png [98.3 KB]
1540350245310.png [223.5 KB]
kafka_3.png [83.6 KB]
s4.PNG [286.5 KB]
ml14.png [98.7 KB]
ml06.png [166.4 KB]
ml27.png [10.5 KB]
1540349692086.png [47.4 KB]
ml08.png [233.1 KB]
ss2.PNG [163.9 KB]
kafka_17.png [129.5 KB]
kafka_11.png [78.6 KB]
kafka_7.png [393.8 KB]
env2.PNG [23.8 KB]
kafka_5.png [253.0 KB]
s10.PNG [79.2 KB]
s13.PNG [297.4 KB]
ml15.png [172.6 KB]
ml21.png [65.4 KB]
kafka_6.png [60.6 KB]
ml12.png [123.2 KB]
kafka_2.png [22.7 KB]
ml25.png [21.3 KB]
ml02.png [119.5 KB]
ss5.PNG [43.9 KB]
ml18.png [180.4 KB]
s7.PNG [339.4 KB]
1540349678122.png [37.2 KB]
ss9.png [69.8 KB]
s2.PNG [16.6 KB]
ml24.png [27.8 KB]
ss7.png [87.9 KB]
env5.png [178.3 KB]
ml33.png [27.4 KB]
ml29.png [94.9 KB]
s6.PNG [102.5 KB]
env1.png [153.3 KB]
s8.PNG [203.5 KB]
ml17.png [87.2 KB]
ss19.PNG [84.7 KB]
ml09.png [76.4 KB]
ml28.png [39.5 KB]
ml07.png [74.2 KB]
kafka_14.png [91.6 KB]
ml13.png [25.2 KB]
s14.PNG [128.0 KB]
ml34.png [9.9 KB]
kafka_4.png [60.6 KB]
kafka_8.png [386.8 KB]
ml22.png [23.7 KB]
ml1.3.md [5.0 KB]
s1.2.html [30.9 KB]
s1.5.md [4.5 KB]
s1.1.html [36.7 KB]
s1.7.md [4.0 KB]
s1.1.md [2.9 KB]
s1.4.md [9.0 KB]
s1.0.html [31.4 KB]
s1.4.html [46.8 KB]
s1.3.html [33.1 KB]
ml1.3.html [39.7 KB]
ml1.2.md [8.6 KB]
ml1.0.md [299.0 B]
ml1.1.html [40.6 KB]
s1.5.html [40.0 KB]
s1.6.html [36.8 KB]
ml1.4.html [35.6 KB]
ml1.0.html [29.7 KB]
s.html [30.2 KB]
s1.0.md [339.0 B]
s1.2.md [791.0 B]
ml1.1.md [4.4 KB]
s1.7.html [37.1 KB]
s1.4 - 副本.md [7.8 KB]
s1.3.md [1.6 KB]
s1.6.md [3.1 KB]
s.md [115.0 B]
ml1.2.html [45.4 KB]
ml1.4.md [3.6 KB]
📁 day09
📁 pics
s3.PNG [86.2 KB]
1540347422756.png [102.2 KB]
s10.PNG [79.2 KB]
kafka_5.png [253.0 KB]
s4.PNG [286.5 KB]
1540347375394(1).png [52.7 KB]
kafka_9.png [57.1 KB]
kafka_7.png [393.8 KB]
s11.PNG [232.2 KB]
s7.PNG [339.4 KB]
1540350260244.png [223.5 KB]
s5.PNG [143.6 KB]
1540350245310.png [223.5 KB]
1540349692086.png [47.4 KB]
1540350201715.png [78.7 KB]
kafka_13.png [222.3 KB]
kafka_4.png [60.6 KB]
1540347254561.png [32.7 KB]
kafka_16.png [51.2 KB]
kafka_11.png [78.6 KB]
kafka_12.png [147.0 KB]
1540350674304.png [21.2 KB]
kafka_2.png [22.7 KB]
s2.PNG [16.6 KB]
kafka_6.png [60.6 KB]
s1.PNG [19.0 KB]
1540347389671.png [52.7 KB]
kafka_10.png [238.6 KB]
kafka_8.png [386.8 KB]
宽依赖和窄依赖.png [250.5 KB]
s12.PNG [305.8 KB]
s8.PNG [203.5 KB]
kafka_15.png [56.2 KB]
s9.PNG [292.5 KB]
s13.PNG [297.4 KB]
kafka_17.png [129.5 KB]
kafka_3.png [83.6 KB]
1540349678122.png [37.2 KB]
s6.PNG [102.5 KB]
kafka_14.png [91.6 KB]
s14.PNG [128.0 KB]
s.md [84.0 B]
s1.4.md [20.8 KB]
s1.2.md [7.8 KB]
s1.0.md [186.0 B]
s1.1.md [2.4 KB]
s1.1.html [35.2 KB]
s1.5.html [52.9 KB]
s1.4.html [62.6 KB]
s1.2.html [47.9 KB]
s.html [29.9 KB]
s1.3.html [43.5 KB]
s1.3.md [6.5 KB]
s1.5.md [7.2 KB]
s1.0.html [30.2 KB]
📁 day06
📁 img
📁 hdfs_read_write
a.jpg [135.6 KB]
e.jpg [156.9 KB]
i.jpg [157.6 KB]
c.jpg [135.7 KB]
b.jpg [138.3 KB]
k.jpg [53.1 KB]
j.jpg [156.4 KB]
g.jpg [155.1 KB]
h.jpg [156.2 KB]
d.jpg [137.8 KB]
image-mapreduce.png [524.6 KB]
zq3.png [86.7 KB]
zq12.png [50.1 KB]
yarn_architecture.gif [32.3 KB]
mp3.png [666.8 KB]
image-hadoop1.png [433.1 KB]
image-yarn.png [656.7 KB]
mp5.png [863.2 KB]
hadoop-hdfsarchitecture.png [39.6 KB]
hadoop-生态.png [396.0 KB]
image-bigdata01.png [546.4 KB]
mp4.png [461.0 KB]
image-大数据应用2.png [1.3 MB]
zq11.png [48.6 KB]
hdfs_arc.png [55.9 KB]
mp1.png [991.2 KB]
yarn4.png [70.9 KB]
zq2.png [19.7 KB]
image-大数据应用3.png [1008.5 KB]
mr_result.png [38.1 KB]
image-MapReduce4.png [335.6 KB]
image-大数据行业应用.png [526.8 KB]
zq14.png [318.3 KB]
image-mapreduce2.png [668.1 KB]
zq6.png [8.5 KB]
zq7.png [132.4 KB]
hadoop-yarn.jpg [34.5 KB]
zq4.png [103.3 KB]
mp6.png [916.5 KB]
zq13.png [148.3 KB]
image-mapreduce1.png [327.3 KB]
image-MapReduce5.png [334.6 KB]
zq5.png [14.0 KB]
zq8.png [3.1 KB]
zq9.png [260.6 KB]
image-yarn2.png [652.6 KB]
image-mapreduce3.png [1.1 MB]
zq1.png [8.1 KB]
hadoop-yarn3.png [96.4 KB]
hadoop-hdfs1.png [29.3 KB]
zq10.png [154.5 KB]
ha3.3.md [2.7 KB]
ha4.2.md [3.3 KB]
ha3.0.md [99.0 B]
ha3.md [334.0 B]
ha4.0.html [29.2 KB]
ha3.0.html [30.7 KB]
ha4.2.html [36.7 KB]
ha4.4.md [5.3 KB]
ha4.4.html [41.0 KB]
ha3.2.md [3.2 KB]
ha4.3.html [35.9 KB]
ha3.4.md [3.3 KB]
ha4.5.md [3.5 KB]
ha4.3.md [3.2 KB]
ha3.html [30.5 KB]
ha3.5.md [7.9 KB]
ha3.1.html [37.5 KB]
ha3.5.html [47.4 KB]
ha4.1.md [9.4 KB]
ha4.5.html [38.6 KB]
ha3.2.html [36.4 KB]
ha4.1.html [50.6 KB]
ha3.1.md [3.6 KB]
ha3.3.html [34.7 KB]
ha4.0.md [119.0 B]
ha3.4.html [37.3 KB]
📁 day07
📁 pics
1540349678122.png [32.9 KB]
1540350245310.png [223.5 KB]
kafka_5.png [253.0 KB]
1540350674304.png [21.2 KB]
k4.PNG [18.2 KB]
kafka_4.png [60.6 KB]
k3.PNG [65.8 KB]
1540347422756.png [102.2 KB]
k1.PNG [19.1 KB]
kafka_17.png [129.5 KB]
kafka_3.png [83.6 KB]
kafka_8.png [386.8 KB]
1540349692086.png [35.3 KB]
kafka_16.png [51.2 KB]
1540350201715.png [78.7 KB]
1540350260244.png [223.5 KB]
kafka_9.png [57.1 KB]
kafka_11.png [78.6 KB]
f1.png [447.0 KB]
k5.PNG [58.4 KB]
kafka_15.png [56.2 KB]
1540347375394.png [52.7 KB]
kafka_2.png [22.7 KB]
宽依赖和窄依赖.png [250.5 KB]
f4.png [22.9 KB]
kafka_6.png [60.6 KB]
1540347254561.png [32.7 KB]
f2.png [114.3 KB]
kafka_12.png [147.0 KB]
kafka_10.png [238.6 KB]
k2.PNG [22.7 KB]
kafka_14.png [91.6 KB]
kafka_7.png [393.8 KB]
kafka_13.png [222.3 KB]
f3.png [36.9 KB]
1540347389671.png [52.7 KB]
f1.3.md [301.0 B]
f1.2.html [37.8 KB]
k1.2.html [38.5 KB]
k1.3.html [37.0 KB]
f1.6.html [39.1 KB]
k1.5.html [36.7 KB]
k1.3.md [3.5 KB]
f1.7.html [45.3 KB]
f1.5.md [10.0 KB]
k1.0.md [454.0 B]
f1.1.html [35.3 KB]
k1.4.md [1.5 KB]
k1.1.md [2.5 KB]
f1.4.md [2.1 KB]
k1.2.md [4.8 KB]
f1.3.html [29.7 KB]
k.md [160.0 B]
f1.6.md [6.7 KB]
f1.0.html [31.5 KB]
k1.4.html [31.4 KB]
k1.5.md [3.1 KB]
f1.4.html [32.7 KB]
f1.5.html [45.2 KB]
k1.1.html [35.8 KB]
f1.1.md [2.5 KB]
f.html [30.6 KB]
f.md [300.0 B]
k1.0.html [29.9 KB]
f1.2.md [3.9 KB]
f1.7.md [10.4 KB]
f1.0.md [382.0 B]
📁 day05
📁 img
📁 hdfs_read_write
e.jpg [156.9 KB]
i.jpg [157.6 KB]
c.jpg [135.7 KB]
h.jpg [156.2 KB]
j.jpg [156.4 KB]
b.jpg [138.3 KB]
g.jpg [155.1 KB]
a.jpg [135.6 KB]
k.jpg [53.1 KB]
d.jpg [137.8 KB]
yarn_architecture.gif [32.3 KB]
image-大数据行业应用.png [526.8 KB]
image-mapreduce3.png [1.1 MB]
mp4.png [461.0 KB]
image-mapreduce1.png [327.3 KB]
yarn4.png [70.9 KB]
mp5.png [863.2 KB]
image-yarn2.png [652.6 KB]
image-bigdata01.png [546.4 KB]
hdfs_arc.png [55.9 KB]
image-mapreduce2.png [668.1 KB]
mp1.png [991.2 KB]
mp3.png [666.8 KB]
hadoop-yarn.jpg [34.5 KB]
image-mapreduce.png [524.6 KB]
image-大数据应用2.png [1.3 MB]
image-hadoop1.png [433.1 KB]
mr_result.png [38.1 KB]
hadoop-yarn3.png [96.4 KB]
image-yarn.png [656.7 KB]
hadoop-hdfs1.png [29.3 KB]
mp6.png [916.5 KB]
image-大数据应用3.png [1008.5 KB]
image-MapReduce5.png [334.6 KB]
hadoop-生态.png [396.0 KB]
hadoop-hdfsarchitecture.png [39.6 KB]
image-MapReduce4.png [335.6 KB]
ha1.5.md [256.0 B]
ha1.3.md [324.0 B]
ha2.7.md [268.0 B]
ha2.5.md [4.5 KB]
ha1.5.html [30.5 KB]
ha1.2.md [1.3 KB]
ha1.1.html [34.0 KB]
ha2.1.html [30.8 KB]
ha1.3.html [29.8 KB]
ha2.3.html [32.0 KB]
ha1.1.md [2.4 KB]
ha2.1.md [412.0 B]
ha1.0.html [31.0 KB]
ha1.2.html [31.7 KB]
ha(1).html [29.9 KB]
ha2.4.html [33.1 KB]
ha2.2.md [522.0 B]
ha2.4.md [1.9 KB]
ha1.0.md [150.0 B]
ha2.2.html [30.1 KB]
ha2.0.html [29.6 KB]
ha2.3.md [1.9 KB]
ha1.4.html [31.4 KB]
ha2.6.html [33.9 KB]
ha2.6.md [2.1 KB]
ha2.0.md [212.0 B]
ha.md [115.0 B]
ha1.4.md [950.0 B]
ha2.7.html [31.2 KB]
ha2.5.html [37.9 KB]
index.html [31.6 KB]
search_index.json [2.0 MB]
📁 day06
📁 img
📁 hdfs_read_write
g.jpg [155.1 KB]
j.jpg [156.4 KB]
d.jpg [137.8 KB]
k.jpg [53.1 KB]
a.jpg [135.6 KB]
c.jpg [135.7 KB]
h.jpg [156.2 KB]
b.jpg [138.3 KB]
i.jpg [157.6 KB]
e.jpg [156.9 KB]
zq14.png [318.3 KB]
zq9.png [260.6 KB]
image-MapReduce5.png [334.6 KB]
zq12.png [50.1 KB]
zq6.png [8.5 KB]
image-hadoop1.png [433.1 KB]
hadoop-生态.png [396.0 KB]
hadoop-hdfs1.png [29.3 KB]
mp5.png [863.2 KB]
zq1.png [8.1 KB]
mp3.png [666.8 KB]
yarn4.png [70.9 KB]
image-mapreduce2.png [668.1 KB]
hdfs_arc.png [55.9 KB]
hadoop-hdfsarchitecture.png [39.6 KB]
hadoop-yarn3.png [96.4 KB]
zq7.png [132.4 KB]
zq10.png [154.5 KB]
image-mapreduce1.png [327.3 KB]
hadoop-yarn.jpg [34.5 KB]
zq8.png [3.1 KB]
image-大数据应用3.png [1008.5 KB]
zq2.png [19.7 KB]
mp1.png [991.2 KB]
image-大数据应用2.png [1.3 MB]
mp6.png [916.5 KB]
yarn_architecture.gif [32.3 KB]
mp4.png [461.0 KB]
image-mapreduce.png [524.6 KB]
image-yarn2.png [652.6 KB]
mr_result.png [38.1 KB]
zq13.png [148.3 KB]
image-yarn.png [656.7 KB]
image-大数据行业应用.png [526.8 KB]
zq5.png [14.0 KB]
zq3.png [86.7 KB]
zq4.png [103.3 KB]
image-mapreduce3.png [1.1 MB]
image-bigdata01.png [546.4 KB]
image-MapReduce4.png [335.6 KB]
zq11.png [48.6 KB]
ha4.1.md [9.4 KB]
ha3.2(1).md [3.2 KB]
ha3.0.md [99.0 B]
ha4.0.md [119.0 B]
ha4.5.md [3.5 KB]
ha3.4.md [3.3 KB]
ha3.5.md [7.9 KB]
ha3.3.md [2.7 KB]
ha3.1.md [3.6 KB]
ha4.4.md [5.3 KB]
ha4.2.md [3.3 KB]
ha3.md [334.0 B]
ha4.3.md [3.2 KB]
SUMMARY.md [3.3 KB]
README.md [498.0 B]
📁 day05
📁 视频
10，hbase的shell操作_.mp4 [107.3 MB]
2，回顾_.mp4 [25.0 MB]
6，hbase介绍_.mp4 [38.9 MB]
5，hive的综合案例_.mp4 [107.2 MB]
9，Hbase的环境配置_.mp4 [51.9 MB]
8，Hbase的数据模型_.mp4 [58.4 MB]
7，上午小结_.mp4 [25.7 MB]
1，反馈总结_.mp4 [7.9 MB]
3，使用已有的jar包演示udf使用过程_.mp4 [47.0 MB]
4，利用python实现udf_.mp4 [13.8 MB]
3.png [167.5 KB]
思路.txt [1.3 KB]
2.png [160.0 KB]
1.png [86.3 KB]
📁 day01
📁 资料
📁 .ipynb_checkpoints
day01-2.ipynb [2.3 MB]
ratings.csv [2.4 MB]
day01-1.ipynb [34.9 KB]
📁 视频1
12，针对于连续型数据的评分算法_.mp4 [23.4 MB]
6，推荐系统的算法流程介绍_.mp4 [49.4 MB]
9，相似度计算案例-1_.mp4 [37.5 MB]
2，课程整体介绍_.mp4 [6.4 MB]
15，推荐系统的冷启动问题_.mp4 [72.5 MB]
10，总结_.mp4 [57.7 MB]
14，推荐系统评估_.mp4 [38.5 MB]
8，相似度算法介绍_.mp4 [56.8 MB]
11，基于用户和基于物品的推荐案例完成_.mp4 [104.6 MB]
13，User-Based的评分预测案例实现_.mp4 [114.5 MB]
4，推荐系统和web项目的区别_.mp4 [21.3 MB]
3，推荐是什么_.mp4 [40.5 MB]
1，学习方法_.mp4 [4.5 MB]
5，推荐系统设计_.mp4 [56.2 MB]
📁 day02
📁 视频
8，上午小结_.mp4 [15.4 MB]
18，总结_.mp4 [45.4 MB]
13，基于内容的推荐算法介绍_.mp4 [23.8 MB]
2，基于模型的协同过滤推荐_.mp4 [50.3 MB]
1，回顾_.mp4 [38.6 MB]
15，获取电影数据集_.mp4 [34.8 MB]
16，获取电影数据集代码实现_.mp4 [33.5 MB]
7，交替最小二乘法原理讲解_.mp4 [10.1 MB]
3，基于模型的协同过滤代码思路整理_.mp4 [26.6 MB]
4，虚拟机环境配置_.mp4 [17.0 MB]
9，基于矩阵分解的发展史_.mp4 [51.0 MB]
5，基于模型的协同过滤代码实现_.mp4 [76.9 MB]
12，BiasSVD原理介绍及其代码实现_.mp4 [10.7 MB]
6，数据划分，准确率评估实现_.mp4 [92.7 MB]
17，物品画像的关键词权重提取代码实现_.mp4 [65.2 MB]
10，LFM算法原理介绍_.mp4 [14.2 MB]
11，LFM代码实现_.mp4 [25.0 MB]
14，tfidf介绍_.mp4 [35.0 MB]
📁 资料
ratings.csv [2.4 MB]
tags.csv [115.9 KB]
movies.csv [482.8 KB]
概述.txt [836.0 B]
📁 day03
📁 资料
资料链接.txt [382.0 B]
📁 视频
2，用户画像的构建_.mp4 [72.3 MB]
1，回顾_.mp4 [31.1 MB]
7，分布式文件系统的设计思路_.mp4 [37.5 MB]
17，MapReduce介绍及其编程流程_.mp4 [21.3 MB]
13，hadoop的shell操作练习_.mp4 [32.0 MB]
20，总结_.mp4 [29.5 MB]
18，MapReduce计算PI体验_.mp4 [24.1 MB]
16，YARN介绍及其YARN架构、执行流程_.mp4 [69.4 MB]
6，hadoop介绍_.mp4 [49.3 MB]
15，hdfs的环境搭建_.mp4 [74.4 MB]
4，用户画像构建_.mp4 [67.1 MB]
8，hadoop核心组件_.mp4 [53.9 MB]
5，为用户推荐topN个电影_.mp4 [47.6 MB]
10，hdfs的使用_.mp4 [28.5 MB]
11，hadoop的shell操作_.mp4 [28.4 MB]
14，hdfs的架构及其优缺点_.mp4 [60.0 MB]
3，倒排索引_.mp4 [53.3 MB]
19，MRJob实现wordcount_.mp4 [98.2 MB]
9，Hadoop的优势_.mp4 [3.1 MB]
12，上午小结_.mp4 [26.0 MB]
📁 day08
📁 视频
9，user_profile缺失值处理-利用随机森林对缺失值进行预测_.mp4 [128.4 MB]
3，申请spark的资源_.mp4 [31.2 MB]
1，作业_.mp4 [56.7 MB]
5，保存数据模型及其召回商品到redis_.mp4 [32.8 MB]
12，CTR模型训练-实现_.mp4 [26.3 MB]
6，raw_sample数据的读取和处理_.mp4 [94.1 MB]
7，ad_feature的数据读取和处理_.mp4 [26.5 MB]
14，结合redis完成商品召回_.mp4 [30.9 MB]
15，完成商品的精选及其总结_.mp4 [100.6 MB]
10，user_profile缺失值处理-低维数据转高维数据_.mp4 [53.3 MB]
8，上午小结_.mp4 [11.0 MB]
13，建立广告类别和广告id的匹配关系_.mp4 [73.1 MB]
2，项目思路整理和数据集切分_.mp4 [38.6 MB]
11，CTR模型训练-数据准备_.mp4 [56.1 MB]
4，spark实现数据的读取和评分数据的构建_.mp4 [132.6 MB]
📁 资料
📁 day05-day10
📁 _book
📁 day07
📁 pics
1540349692086.png [35.3 KB]
1540350674304.png [21.2 KB]
kafka_6.png [60.6 KB]
k3.PNG [65.8 KB]
kafka_3.png [83.6 KB]
f4.png [22.9 KB]
kafka_8.png [386.8 KB]
k5.PNG [58.4 KB]
宽依赖和窄依赖.png [250.5 KB]
kafka_15.png [56.2 KB]
1540350245310.png [223.5 KB]
kafka_16.png [51.2 KB]
kafka_11.png [78.6 KB]
1540350260244.png [223.5 KB]
1540347254561.png [32.7 KB]
kafka_13.png [222.3 KB]
1540347389671.png [52.7 KB]
1540349678122.png [32.9 KB]
f2.png [114.3 KB]
kafka_9.png [57.1 KB]
kafka_7.png [393.8 KB]
kafka_12.png [147.0 KB]
1540347422756.png [102.2 KB]
k1.PNG [19.1 KB]
f3.png [36.9 KB]
kafka_2.png [22.7 KB]
f1.png [447.0 KB]
1540350201715.png [78.7 KB]
k2.PNG [22.7 KB]
1540347375394.png [52.7 KB]
kafka_4.png [60.6 KB]
kafka_10.png [238.6 KB]
kafka_5.png [253.0 KB]
k4.PNG [18.2 KB]
kafka_17.png [129.5 KB]
kafka_14.png [91.6 KB]
f1.4.html [32.7 KB]
f1.1.html [35.3 KB]
f1.2.md [3.9 KB]
f.html [30.6 KB]
f1.7.md [10.4 KB]
k1.1.md [2.5 KB]
k1.2.html [38.5 KB]
f1.4.md [2.1 KB]
f1.0.md [382.0 B]
f1.5.html [45.2 KB]
f1.7.html [45.3 KB]
f1.6.html [39.1 KB]
f1.2.html [37.8 KB]
f1.5.md [10.0 KB]
k1.5.html [36.7 KB]
k1.0.md [454.0 B]
k1.3.md [3.5 KB]
k1.5.md [3.1 KB]
k.md [160.0 B]
k1.4.html [31.4 KB]
f1.3.md [301.0 B]
k1.4.md [1.5 KB]
f1.6.md [6.7 KB]
f1.3.html [29.7 KB]
k1.1.html [35.8 KB]
f1.0.html [31.5 KB]
f1.1.md [2.5 KB]
k1.0.html [29.9 KB]
f.md [300.0 B]
k1.3.html [37.0 KB]
k1.2.md [4.8 KB]
📁 day10
📁 pics
s2.PNG [16.6 KB]
s9.PNG [292.5 KB]
s4.PNG [286.5 KB]
ss4.PNG [165.9 KB]
ml25.png [21.3 KB]
s7.PNG [339.4 KB]
ml37.png [45.5 KB]
kafka_10.png [238.6 KB]
ml11.png [174.8 KB]
ml14.png [98.7 KB]
ml23.png [10.1 KB]
宽依赖和窄依赖.png [250.5 KB]
ml18.png [180.4 KB]
kafka_9.png [57.1 KB]
s5.PNG [143.6 KB]
1540347389671.png [52.7 KB]
kafka_3.png [83.6 KB]
kafka_4.png [60.6 KB]
ml26.png [137.7 KB]
s1.PNG [19.0 KB]
ss3.PNG [376.6 KB]
ss8.PNG [296.5 KB]
kafka_15.png [56.2 KB]
ss6.png [163.3 KB]
1540350260244.png [223.5 KB]
1540347422756.png [102.2 KB]
kafka_16.png [51.2 KB]
ml09.png [76.4 KB]
ml31.png [95.6 KB]
ml03.png [97.6 KB]
ss9.png [69.8 KB]
kafka_2.png [22.7 KB]
ss10.png [52.1 KB]
ml22.png [23.7 KB]
ml30.png [260.2 KB]
ss12.png [98.3 KB]
ml35.png [11.8 KB]
ml28.png [39.5 KB]
1540349692086.png [47.4 KB]
ml15.png [172.6 KB]
1540349678122.png [37.2 KB]
kafka_7.png [393.8 KB]
env5.png [178.3 KB]
1540347254561.png [32.7 KB]
ml16.png [28.7 KB]
ss7.png [87.9 KB]
ss5.PNG [43.9 KB]
s8.PNG [203.5 KB]
ss18.PNG [398.8 KB]
ml08.png [233.1 KB]
ss15.png [157.0 KB]
ss17.png [72.8 KB]
s10.PNG [79.2 KB]
ml29.png [94.9 KB]
env2.PNG [23.8 KB]
ss16.png [85.1 KB]
ml36.png [187.9 KB]
ml06.png [166.4 KB]
kafka_14.png [91.6 KB]
1540347375394(1).png [52.7 KB]
ml04.png [103.7 KB]
ss13.png [166.8 KB]
ml02.png [119.5 KB]
ss1.png [328.2 KB]
kafka_17.png [129.5 KB]
ml05.png [83.5 KB]
ss11.png [367.8 KB]
ss19.PNG [84.7 KB]
env4.png [191.5 KB]
kafka_8.png [386.8 KB]
s11.PNG [232.2 KB]
ss14.png [101.1 KB]
s12.PNG [305.8 KB]
ml21.png [65.4 KB]
ml17.png [87.2 KB]
ml33.png [27.4 KB]
kafka_11.png [78.6 KB]
env1.png [153.3 KB]
ml20.png [40.7 KB]
ml13.png [25.2 KB]
kafka_6.png [60.6 KB]
ml34.png [9.9 KB]
1540350245310.png [223.5 KB]
env3.PNG [20.6 KB]
1540350674304.png [21.2 KB]
s3.PNG [86.2 KB]
1540350201715.png [78.7 KB]
kafka_5.png [253.0 KB]
kafka_12.png [147.0 KB]
ml12.png [123.2 KB]
ss2.PNG [163.9 KB]
ml27.png [10.5 KB]
ml32.png [16.7 KB]
s13.PNG [297.4 KB]
ml24.png [27.8 KB]
ml19.png [20.7 KB]
kafka_13.png [222.3 KB]
s14.PNG [128.0 KB]
ml01.png [66.3 KB]
ml07.png [74.2 KB]
s1.7.html [37.1 KB]
ml1.0.html [29.7 KB]
ml1.1.md [4.4 KB]
s1.3.html [33.1 KB]
s1.4.html [46.8 KB]
s1.5.md [4.5 KB]
ml1.4.md [3.6 KB]
s1.1.html [36.7 KB]
s1.4 - 副本.md [7.8 KB]
s1.6.html [36.8 KB]
s1.3.md [1.6 KB]
s1.0.md [339.0 B]
s1.2.html [30.9 KB]
ml1.2.html [45.4 KB]
s1.0.html [31.4 KB]
ml1.0.md [299.0 B]
s.md [115.0 B]
s1.5.html [40.0 KB]
s1.1.md [2.9 KB]
ml1.2.md [8.6 KB]
ml1.1.html [40.6 KB]
s1.2.md [791.0 B]
s1.4.md [9.0 KB]
ml1.3.md [5.0 KB]
ml1.3.html [39.7 KB]
s1.7.md [4.0 KB]
s.html [30.2 KB]
s1.6.md [3.1 KB]
ml1.4.html [35.6 KB]
📁 day05
📁 img
📁 hdfs_read_write
d.jpg [137.8 KB]
i.jpg [157.6 KB]
j.jpg [156.4 KB]
k.jpg [53.1 KB]
e.jpg [156.9 KB]
g.jpg [155.1 KB]
b.jpg [138.3 KB]
a.jpg [135.6 KB]
c.jpg [135.7 KB]
h.jpg [156.2 KB]
mp1.png [991.2 KB]
hdfs_arc.png [55.9 KB]
image-yarn2.png [652.6 KB]
image-mapreduce3.png [1.1 MB]
image-mapreduce.png [524.6 KB]
hadoop-hdfs1.png [29.3 KB]
image-yarn.png [656.7 KB]
yarn4.png [70.9 KB]
yarn_architecture.gif [32.3 KB]
mp3.png [666.8 KB]
mp4.png [461.0 KB]
hadoop-yarn3.png [96.4 KB]
mp6.png [916.5 KB]
image-MapReduce5.png [334.6 KB]
hadoop-hdfsarchitecture.png [39.6 KB]
image-hadoop1.png [433.1 KB]
image-大数据应用2.png [1.3 MB]
image-MapReduce4.png [335.6 KB]
mr_result.png [38.1 KB]
hadoop-yarn.jpg [34.5 KB]
hadoop-生态.png [396.0 KB]
image-mapreduce1.png [327.3 KB]
image-mapreduce2.png [668.1 KB]
image-大数据行业应用.png [526.8 KB]
image-大数据应用3.png [1008.5 KB]
image-bigdata01.png [546.4 KB]
mp5.png [863.2 KB]
ha2.0.md [212.0 B]
ha2.6.html [33.9 KB]
ha2.2.html [30.1 KB]
ha2.3.html [32.0 KB]
ha2.1.md [412.0 B]
ha2.7.html [31.2 KB]
ha2.5.html [37.9 KB]
ha1.2.md [1.3 KB]
ha2.5.md [4.5 KB]
ha2.2.md [522.0 B]
ha1.4.html [31.4 KB]
ha1.4.md [950.0 B]
ha2.0.html [29.6 KB]
ha1.0.html [31.0 KB]
ha.md [115.0 B]
ha1.5.md [256.0 B]
ha1.1.md [2.4 KB]
ha2.1.html [30.8 KB]
ha1.1.html [34.0 KB]
ha2.4.md [1.9 KB]
ha2.6.md [2.1 KB]
ha1.3.md [324.0 B]
ha2.7.md [268.0 B]
ha2.4.html [33.1 KB]
ha.html [29.9 KB]
ha1.3.html [29.8 KB]
ha2.3.md [1.9 KB]
ha1.0.md [150.0 B]
ha1.2.html [31.7 KB]
ha1.5.html [30.5 KB]
📁 day06
📁 img
📁 hdfs_read_write
i.jpg [157.6 KB]
g.jpg [155.1 KB]
e.jpg [156.9 KB]
j.jpg [156.4 KB]
k.jpg [53.1 KB]
d.jpg [137.8 KB]
h.jpg [156.2 KB]
a.jpg [135.6 KB]
c.jpg [135.7 KB]
b.jpg [138.3 KB]
image-bigdata01.png [546.4 KB]
zq9.png [260.6 KB]
zq1.png [8.1 KB]
image-hadoop1.png [433.1 KB]
image-mapreduce2.png [668.1 KB]
image-大数据行业应用.png [526.8 KB]
hadoop-yarn.jpg [34.5 KB]
zq7.png [132.4 KB]
mr_result.png [38.1 KB]
hadoop-hdfsarchitecture.png [39.6 KB]
zq11.png [48.6 KB]
mp1.png [991.2 KB]
zq10.png [154.5 KB]
zq4.png [103.3 KB]
hdfs_arc.png [55.9 KB]
yarn4.png [70.9 KB]
image-大数据应用3.png [1008.5 KB]
mp5.png [863.2 KB]
zq3.png [86.7 KB]
image-MapReduce4.png [335.6 KB]
zq6.png [8.5 KB]
image-mapreduce1.png [327.3 KB]
mp4.png [461.0 KB]
mp3.png [666.8 KB]
image-mapreduce3.png [1.1 MB]
zq5.png [14.0 KB]
mp6.png [916.5 KB]
image-mapreduce.png [524.6 KB]
image-yarn2.png [652.6 KB]
zq13.png [148.3 KB]
zq2.png [19.7 KB]
image-yarn.png [656.7 KB]
image-MapReduce5.png [334.6 KB]
hadoop-yarn3.png [96.4 KB]
hadoop-hdfs1.png [29.3 KB]
zq12.png [50.1 KB]
hadoop-生态.png [396.0 KB]
image-大数据应用2.png [1.3 MB]
yarn_architecture.gif [32.3 KB]
zq8.png [3.1 KB]
zq14.png [318.3 KB]
ha4.4.md [5.3 KB]
ha4.1.md [9.4 KB]
ha4.3(1).md [3.2 KB]
ha3.5.md [7.9 KB]
ha3.1.md [3.6 KB]
ha3.4.html [37.3 KB]
ha4.0.html [29.2 KB]
ha4.3.html [35.9 KB]
ha3.md [334.0 B]
ha3.4.md [3.3 KB]
ha4.5(1).md [3.5 KB]
ha4.2.html [36.7 KB]
ha4.5.html [38.6 KB]
ha3.3.md [2.7 KB]
ha4.4(1).md [5.3 KB]
ha3.1.html [37.5 KB]
ha3.2.html [36.4 KB]
ha4.3.md [3.2 KB]
ha4.1.html [50.6 KB]
ha3.html [30.5 KB]
ha3.3.html [34.7 KB]
ha3.0.html [30.7 KB]
ha4.2.md [3.3 KB]
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ha4.0.md [119.0 B]
ha3.5.html [47.4 KB]
ha3.0.md [99.0 B]
ha4.4.html [41.0 KB]
ha3.2.md [3.2 KB]
📁 day09
📁 pics
kafka_3.png [83.6 KB]
1540347375394.png [52.7 KB]
s13.PNG [297.4 KB]
kafka_6.png [60.6 KB]
kafka_17.png [129.5 KB]
kafka_2.png [22.7 KB]
s5.PNG [143.6 KB]
kafka_12.png [147.0 KB]
kafka_11.png [78.6 KB]
s8.PNG [203.5 KB]
s7.PNG [339.4 KB]
s1.PNG [19.0 KB]
1540350674304.png [21.2 KB]
1540347422756.png [102.2 KB]
kafka_4.png [60.6 KB]
1540349692086.png [47.4 KB]
1540350201715.png [78.7 KB]
s12.PNG [305.8 KB]
s9.PNG [292.5 KB]
1540350245310.png [223.5 KB]
kafka_10.png [238.6 KB]
1540350260244.png [223.5 KB]
kafka_7.png [393.8 KB]
s4.PNG [286.5 KB]
s11.PNG [232.2 KB]
1540349678122.png [37.2 KB]
s6.PNG [102.5 KB]
宽依赖和窄依赖.png [250.5 KB]
kafka_16.png [51.2 KB]
s14.PNG [128.0 KB]
s2.PNG [16.6 KB]
kafka_8.png [386.8 KB]
kafka_9.png [57.1 KB]
kafka_14.png [91.6 KB]
s10.PNG [79.2 KB]
kafka_15.png [56.2 KB]
1540347254561.png [32.7 KB]
kafka_5.png [253.0 KB]
s3.PNG [86.2 KB]
1540347389671.png [52.7 KB]
kafka_13.png [222.3 KB]
s1.2.md [7.8 KB]
s1.0.md [186.0 B]
s1.5.html [52.9 KB]
s1.1.html [35.2 KB]
s1.5.md [7.2 KB]
s1.4.html [62.6 KB]
s1.0.html [30.2 KB]
s.md [84.0 B]
s1.1.md [2.4 KB]
s1.4.md [20.8 KB]
s1.2.html [47.9 KB]
s.html [29.9 KB]
s1.3.md [6.5 KB]
s1.3.html [43.5 KB]
📁 gitbook
📁 fonts
📁 fontawesome
FontAwesome.otf [122.1 KB]
fontawesome-webfont.woff2 [70.2 KB]
fontawesome-webfont.eot [74.7 KB]
fontawesome-webfont.svg [382.4 KB]
fontawesome-webfont.ttf [149.2 KB]
fontawesome-webfont.woff [88.3 KB]
📁 gitbook-plugin-search
search.js [6.2 KB]
lunr.min.js [14.7 KB]
search-engine.js [1.2 KB]
search.css [974.0 B]
📁 images
apple-touch-icon-precomposed-152.png [4.7 KB]
favicon.ico [4.2 KB]
📁 gitbook-plugin-fontsettings
website.css [8.4 KB]
fontsettings.js [6.3 KB]
📁 gitbook-plugin-lunr
lunr.min.js [14.7 KB]
search-lunr.js [1.6 KB]
📁 gitbook-plugin-livereload
plugin.js [327.0 B]
📁 gitbook-plugin-sharing
buttons.js [2.8 KB]
📁 gitbook-plugin-highlight
website.css [30.7 KB]
ebook.css [2.8 KB]
gitbook.js [102.9 KB]
theme.js [110.6 KB]
style.css [51.5 KB]
📁 day08
📁 资料
user.txt [150.0 B]
ip.txt [13.7 MB]
access.log [2.9 MB]
20090121000132.394251.http.format [1.9 MB]
📁 pics
1540350201715.png [78.7 KB]
kafka_14.png [91.6 KB]
kafka_4.png [60.6 KB]
1540347422756.png [102.2 KB]
s7.PNG [339.4 KB]
1540347375394(1).png [52.7 KB]
s2.PNG [16.6 KB]
1540349678122.png [37.2 KB]
1540350674304.png [21.2 KB]
spark1.PNG [15.4 KB]
kafka_2.png [22.7 KB]
s8.PNG [203.5 KB]
kafka_16.png [51.2 KB]
宽依赖和窄依赖.png [250.5 KB]
kafka_17.png [129.5 KB]
kafka_5.png [253.0 KB]
s3.PNG [86.2 KB]
spark3.PNG [90.6 KB]
s1.PNG [19.0 KB]
s6.PNG [102.5 KB]
kafka_6.png [60.6 KB]
kafka_9.png [57.1 KB]
kafka_15.png [56.2 KB]
kafka_10.png [238.6 KB]
1540347389671.png [52.7 KB]
1540350260244.png [223.5 KB]
kafka_13.png [222.3 KB]
1540349692086.png [47.4 KB]
kafka_8.png [386.8 KB]
kafka_3.png [83.6 KB]
1540347254561.png [32.7 KB]
1540350245310.png [223.5 KB]
spark2.PNG [12.0 KB]
kafka_7.png [393.8 KB]
kafka_11.png [78.6 KB]
kafka_12.png [147.0 KB]
s4.PNG [286.5 KB]
s5.PNG [143.6 KB]
s1.3.md [655.0 B]
s1.5.md [2.7 KB]
s1.2.html [33.0 KB]
s1.6.md [4.8 KB]
s1.1.html [48.7 KB]
s1.5.html [36.7 KB]
s1.4.md [4.7 KB]
s1.4.html [41.2 KB]
s1.0.html [30.4 KB]
s1.6.html [42.1 KB]
s.md [71.0 B]
s1.1.md [8.4 KB]
s1.2.md [1.4 KB]
s.html [30.0 KB]
s1.3.html [30.5 KB]
s1.0.md [242.0 B]
index.html [31.6 KB]
search_index.json [2.0 MB]
📁 day10
📁 pics
📁 a
s9.PNG [292.5 KB]
kafka_16.png [51.2 KB]
1540350674304.png [21.2 KB]
ml08.png [233.1 KB]
ml05.png [83.5 KB]
1540349692086.png [47.4 KB]
ml23.png [10.1 KB]
kafka_15.png [56.2 KB]
env4.png [191.5 KB]
ss16.png [85.1 KB]
ss11.png [367.8 KB]
ml25.png [21.3 KB]
1540347254561.png [32.7 KB]
s5.PNG [143.6 KB]
kafka_9.png [57.1 KB]
kafka_8.png [386.8 KB]
kafka_17.png [129.5 KB]
kafka_12.png [147.0 KB]
ml11.png [174.8 KB]
ml33.png [27.4 KB]
1540349678122.png [37.2 KB]
ml22.png [23.7 KB]
s14.PNG [128.0 KB]
宽依赖和窄依赖.png [250.5 KB]
s13.PNG [297.4 KB]
ss1.png [328.2 KB]
kafka_6.png [60.6 KB]
kafka_3.png [83.6 KB]
ml21.png [65.4 KB]
ss9.png [69.8 KB]
1540347375394.png [52.7 KB]
kafka_11.png [78.6 KB]
ml17.png [87.2 KB]
1540350245310.png [223.5 KB]
ss8.PNG [296.5 KB]
ml24.png [27.8 KB]
s6.PNG [102.5 KB]
ml15.png [172.6 KB]
s3.PNG [86.2 KB]
ml26.png [137.7 KB]
s2.PNG [16.6 KB]
ss15.png [157.0 KB]
ml01.png [66.3 KB]
s8.PNG [203.5 KB]
s1.PNG [19.0 KB]
ss5.PNG [43.9 KB]
ss19.PNG [84.7 KB]
ss18.PNG [398.8 KB]
kafka_5.png [253.0 KB]
kafka_2.png [22.7 KB]
env1.png [153.3 KB]
ml07.png [74.2 KB]
ss12.png [98.3 KB]
ml09.png [76.4 KB]
ml35.png [11.8 KB]
ml14.png [98.7 KB]
ml02.png [119.5 KB]
ml03.png [97.6 KB]
ss7.png [87.9 KB]
ss4.PNG [165.9 KB]
ml13.png [25.2 KB]
1540350260244.png [223.5 KB]
ml32.png [16.7 KB]
ss10.png [52.1 KB]
ml36.png [187.9 KB]
ml16.png [28.7 KB]
kafka_14.png [91.6 KB]
ml37.png [45.5 KB]
env5.png [178.3 KB]
ss3.PNG [376.6 KB]
kafka_10.png [238.6 KB]
env2.PNG [23.8 KB]
kafka_13.png [222.3 KB]
ml10.png [215.3 KB]
kafka_4.png [60.6 KB]
1540350201715.png [78.7 KB]
ml30.png [260.2 KB]
s7.PNG [339.4 KB]
1540347389671.png [52.7 KB]
s11.PNG [232.2 KB]
kafka_7.png [393.8 KB]
ml29.png [94.9 KB]
1540347422756.png [102.2 KB]
ml06.png [166.4 KB]
ml04.png [103.7 KB]
ss17.png [72.8 KB]
s4.PNG [286.5 KB]
ml28.png [39.5 KB]
ss13.png [166.8 KB]
ss2.PNG [163.9 KB]
ml31.png [95.6 KB]
s12.PNG [305.8 KB]
ml20.png [40.7 KB]
ss14.png [101.1 KB]
ml27.png [10.5 KB]
s10.PNG [79.2 KB]
ml12.png [123.2 KB]
ml34.png [9.9 KB]
env3.PNG [20.6 KB]
s1.7.md [4.0 KB]
s1.4 - 副本.md [7.8 KB]
ml1.3.md [5.0 KB]
ml1.4.md [3.6 KB]
s1.4.md [9.0 KB]
ml1.1.md [4.4 KB]
s.md [115.0 B]
s1.6.md [3.1 KB]
s1.2.md [791.0 B]
s1.1.md [2.9 KB]
s1.3.md [1.6 KB]
s1.0.md [339.0 B]
ml1.0.md [299.0 B]
s1.5.md [4.5 KB]
ml1.2.md [8.6 KB]
📁 day09
📁 pics
1540350674304.png [21.2 KB]
s9.PNG [292.5 KB]
kafka_13.png [222.3 KB]
1540350245310.png [223.5 KB]
s6.PNG [102.5 KB]
1540347389671.png [52.7 KB]
kafka_5.png [253.0 KB]
s7.PNG [339.4 KB]
kafka_2.png [22.7 KB]
宽依赖和窄依赖.png [250.5 KB]
kafka_7.png [393.8 KB]
1540347422756.png [102.2 KB]
s5.PNG [143.6 KB]
kafka_9.png [57.1 KB]
s14.PNG [128.0 KB]
1540349692086.png [47.4 KB]
1540349678122.png [37.2 KB]
1540350260244.png [223.5 KB]
1540347254561.png [32.7 KB]
kafka_15.png [56.2 KB]
s13.PNG [297.4 KB]
kafka_17.png [129.5 KB]
kafka_11.png [78.6 KB]
1540350201715.png [78.7 KB]
kafka_16.png [51.2 KB]
1540347375394.png [52.7 KB]
kafka_4.png [60.6 KB]
s2.PNG [16.6 KB]
s10.PNG [79.2 KB]
kafka_10.png [238.6 KB]
s8.PNG [203.5 KB]
s1.PNG [19.0 KB]
kafka_14.png [91.6 KB]
kafka_8.png [386.8 KB]
kafka_6.png [60.6 KB]
kafka_3.png [83.6 KB]
s3.PNG [86.2 KB]
s12.PNG [305.8 KB]
s4.PNG [286.5 KB]
kafka_12.png [147.0 KB]
s11.PNG [232.2 KB]
s1.4.md [20.8 KB]
s1.3.md [6.5 KB]
s1.0.md [186.0 B]
s1.1.md [2.4 KB]
s1.2.md [7.8 KB]
s.md [84.0 B]
s1.5.md [7.2 KB]
📁 day06
📁 img
📁 hdfs_read_write
g.jpg [155.1 KB]
b.jpg [138.3 KB]
k.jpg [53.1 KB]
e.jpg [156.9 KB]
h.jpg [156.2 KB]
c.jpg [135.7 KB]
d.jpg [137.8 KB]
a.jpg [135.6 KB]
i.jpg [157.6 KB]
j.jpg [156.4 KB]
image-mapreduce1.png [327.3 KB]
hadoop-生态.png [396.0 KB]
zq3.png [86.7 KB]
image-mapreduce3.png [1.1 MB]
zq8.png [3.1 KB]
image-mapreduce.png [524.6 KB]
image-大数据应用3.png [1008.5 KB]
zq9.png [260.6 KB]
mp4.png [461.0 KB]
image-MapReduce4.png [335.6 KB]
mp3.png [666.8 KB]
mp5.png [863.2 KB]
image-mapreduce2.png [668.1 KB]
zq1.png [8.1 KB]
zq6.png [8.5 KB]
zq2.png [19.7 KB]
hadoop-yarn.jpg [34.5 KB]
zq11.png [48.6 KB]
image-大数据应用2.png [1.3 MB]
mr_result.png [38.1 KB]
hadoop-hdfsarchitecture.png [39.6 KB]
image-大数据行业应用.png [526.8 KB]
hadoop-yarn3.png [96.4 KB]
mp1.png [991.2 KB]
zq10.png [154.5 KB]
image-MapReduce5.png [334.6 KB]
image-yarn2.png [652.6 KB]
zq5.png [14.0 KB]
image-hadoop1.png [433.1 KB]
zq4.png [103.3 KB]
yarn4.png [70.9 KB]
hadoop-hdfs1.png [29.3 KB]
zq14.png [318.3 KB]
hdfs_arc.png [55.9 KB]
zq7.png [132.4 KB]
image-bigdata01.png [546.4 KB]
mp6.png [916.5 KB]
image-yarn.png [656.7 KB]
zq12.png [50.1 KB]
zq13.png [148.3 KB]
yarn_architecture.gif [32.3 KB]
ha3.4.md [3.3 KB]
ha3.md [334.0 B]
ha3.1.md [3.6 KB]
ha4.4.md [5.3 KB]
ha4.2.md [3.3 KB]
ha4.0.md [119.0 B]
ha4.1.md [9.4 KB]
ha3.2.md [3.2 KB]
ha3.3.md [2.7 KB]
ha4.5.md [3.5 KB]
ha3.5.md [7.9 KB]
ha3.0.md [99.0 B]
ha4.3.md [3.2 KB]
📁 day07
📁 pics
f3.png [36.9 KB]
f2.png [114.3 KB]
kafka_14.png [91.6 KB]
1540347422756.png [102.2 KB]
1540350674304.png [21.2 KB]
kafka_11.png [78.6 KB]
kafka_17.png [129.5 KB]
1540347389671.png [52.7 KB]
1540350245310.png [223.5 KB]
kafka_12.png [147.0 KB]
1540349678122.png [32.9 KB]
kafka_2.png [22.7 KB]
kafka_5.png [253.0 KB]
k5.PNG [58.4 KB]
kafka_6.png [60.6 KB]
f1.png [447.0 KB]
kafka_4.png [60.6 KB]
1540349692086.png [35.3 KB]
kafka_10.png [238.6 KB]
k4.PNG [18.2 KB]
1540350201715.png [78.7 KB]
k2.PNG [22.7 KB]
f4.png [22.9 KB]
kafka_9.png [57.1 KB]
kafka_7.png [393.8 KB]
k1.PNG [19.1 KB]
kafka_16.png [51.2 KB]
kafka_8.png [386.8 KB]
kafka_3.png [83.6 KB]
1540350260244.png [223.5 KB]
宽依赖和窄依赖.png [250.5 KB]
k3.PNG [65.8 KB]
kafka_15.png [56.2 KB]
1540347375394.png [52.7 KB]
kafka_13.png [222.3 KB]
1540347254561.png [32.7 KB]
k1.3.md [3.5 KB]
f1.0.md [382.0 B]
k1.2.md [4.8 KB]
f.md [300.0 B]
k1.4.md [1.5 KB]
k.md [160.0 B]
f1.3.md [301.0 B]
f1.5.md [10.0 KB]
k1.5.md [3.1 KB]
f1.2.md [3.9 KB]
k1.0.md [454.0 B]
k1.1.md [2.5 KB]
f1.7.md [10.4 KB]
f1.4.md [2.1 KB]
f1.6.md [6.7 KB]
f1.1.md [2.5 KB]
📁 day08
📁 资料
ip.txt [13.7 MB]
20090121000132.394251.http.format [1.9 MB]
access.log [2.9 MB]
user.txt [150.0 B]
📁 pics
kafka_7.png [393.8 KB]
kafka_12(1).png [147.0 KB]
kafka_6.png [60.6 KB]
1540349692086.png [47.4 KB]
1540347254561.png [32.7 KB]
1540347422756(1).png [102.2 KB]
kafka_11.png [78.6 KB]
kafka_4(1).png [60.6 KB]
kafka_15(1).png [56.2 KB]
1540350260244(1).png [223.5 KB]
kafka_16.png [51.2 KB]
1540350674304.png [21.2 KB]
kafka_11(1).png [78.6 KB]
s6.PNG [102.5 KB]
s3.PNG [86.2 KB]
1540347389671.png [52.7 KB]
s8.PNG [203.5 KB]
1540349678122(1).png [37.2 KB]
kafka_3.png [83.6 KB]
kafka_4.png [60.6 KB]
kafka_13(1).png [222.3 KB]
kafka_17.png [129.5 KB]
kafka_16(1).png [51.2 KB]
1540350260244.png [223.5 KB]
1540349692086(1).png [47.4 KB]
1540347375394.png [52.7 KB]
1540350245310(1).png [223.5 KB]
1540350245310.png [223.5 KB]
1540347389671(1).png [52.7 KB]
kafka_14.png [91.6 KB]
s2.PNG [16.6 KB]
1540350674304(1).png [21.2 KB]
kafka_14(1).png [91.6 KB]
spark2.PNG [12.0 KB]
s5.PNG [143.6 KB]
s4.PNG [286.5 KB]
kafka_13.png [222.3 KB]
kafka_17(1).png [129.5 KB]
s1.PNG [19.0 KB]
1540350201715(1).png [78.7 KB]
kafka_3(1).png [83.6 KB]
1540347254561(1).png [32.7 KB]
kafka_9.png [57.1 KB]
kafka_10(1).png [238.6 KB]
1540347375394(1).png [52.7 KB]
kafka_5.png [253.0 KB]
spark1.PNG [15.4 KB]
1540347422756.png [102.2 KB]
kafka_8.png [386.8 KB]
s7.PNG [339.4 KB]
kafka_12.png [147.0 KB]
1540350201715.png [78.7 KB]
kafka_15.png [56.2 KB]
1540349678122.png [37.2 KB]
kafka_10.png [238.6 KB]
kafka_2.png [22.7 KB]
spark3.PNG [90.6 KB]
宽依赖和窄依赖.png [250.5 KB]
s1.3.md [655.0 B]
s.md [71.0 B]
s1.4.md [4.7 KB]
s1.2.md [1.4 KB]
s1.0.md [242.0 B]
s1.5.md [2.7 KB]
s1.6.md [4.8 KB]
s1.1.md [8.4 KB]
📁 day05
📁 img
📁 hdfs_read_write
h.jpg [156.2 KB]
c.jpg [135.7 KB]
k.jpg [53.1 KB]
e.jpg [156.9 KB]
g.jpg [155.1 KB]
d.jpg [137.8 KB]
i.jpg [157.6 KB]
a.jpg [135.6 KB]
j.jpg [156.4 KB]
b.jpg [138.3 KB]
yarn4.png [70.9 KB]
hadoop-hdfsarchitecture.png [39.6 KB]
image-hadoop1.png [433.1 KB]
yarn_architecture.gif [32.3 KB]
mp6.png [916.5 KB]
hadoop-hdfs1.png [29.3 KB]
image-MapReduce5.png [334.6 KB]
image-mapreduce.png [524.6 KB]
mp1.png [991.2 KB]
image-大数据应用3.png [1008.5 KB]
image-bigdata01.png [546.4 KB]
hdfs_arc.png [55.9 KB]
image-mapreduce3.png [1.1 MB]
mp3.png [666.8 KB]
hadoop-yarn.jpg [34.5 KB]
mp5.png [863.2 KB]
image-大数据行业应用.png [526.8 KB]
image-yarn.png [656.7 KB]
image-MapReduce4.png [335.6 KB]
hadoop-yarn3.png [96.4 KB]
image-mapreduce2.png [668.1 KB]
image-mapreduce1.png [327.3 KB]
mr_result.png [38.1 KB]
image-大数据应用2.png [1.3 MB]
image-yarn2.png [652.6 KB]
hadoop-生态.png [396.0 KB]
mp4.png [461.0 KB]
ha1.3.md [324.0 B]
ha2.2.md [522.0 B]
ha2.5.md [4.5 KB]
ha1.4.md [950.0 B]
ha2.7.md [268.0 B]
ha.md [115.0 B]
ha1.1.md [2.4 KB]
ha2.4.md [1.9 KB]
ha2.6.md [2.1 KB]
ha2.3.md [1.9 KB]
ha2.1.md [412.0 B]
ha1.5.md [256.0 B]
ha1.2.md [1.3 KB]
ha2.0.md [212.0 B]
ha1.0.md [150.0 B]
README.md [498.0 B]
SUMMARY.md [3.3 KB]
📁 day11-day17
📁 day11_12
📁 img
recommend7.jpeg [13.1 KB]
similarity_calc12.png [104.2 KB]
并行式-加权式.jpeg [129.9 KB]
lambda3.png [167.0 KB]
RS基础业务架构.png [343.2 KB]
als1.png [183.0 KB]
similarity_calc3.png [78.0 KB]
similarity_calc7.png [27.7 KB]
基于物品的预测公式.jpg [22.5 KB]
Rocchio-1.jpg [18.5 KB]
algorithm4.png [101.5 KB]
基础CB推荐算法.jpg [18.2 KB]
similarity_calc1.png [21.5 KB]
recommend2.png [61.4 KB]
algorithm6.png [238.0 KB]
lambda1.png [136.6 KB]
algorithm7.png [308.0 KB]
similarity_calc10.png [64.9 KB]
推荐流程.png [16.9 KB]
并行式-切换式.jpeg [153.7 KB]
相似度计算示例.png [23.9 KB]
协同推荐评分数据集.jpg [65.8 KB]
基于用户的预测公式.jpg [18.6 KB]
firststart1.png [537.2 KB]
lambda2.png [199.9 KB]
RS基础技术架构.png [1.1 MB]
user-itemMatrix2.png [86.2 KB]
1545049355235.png [86.6 KB]
similarity_calc8.png [42.6 KB]
整体式-特征混合.jpeg [105.2 KB]
knn1.png [63.8 KB]
推荐知识库示例.jpeg [160.7 KB]
graph1.png [57.8 KB]
整体式混合方法.jpeg [103.6 KB]
CF介绍.png [178.0 KB]
挖掘频繁项集.png [102.8 KB]
similarity_calc11.png [64.4 KB]
similarity_calc14.png [24.5 KB]
similarity_calc15.png [24.1 KB]
similarity_calc9.png [56.7 KB]
隐因子模型介绍.jpg [158.2 KB]
user-itemMatrix3.png [37.9 KB]
recommend5.png [250.6 KB]
lambda6.png [85.4 KB]
od.png [10.6 KB]
spark02.PNG [25.1 KB]
Rocchio-3.jpg [28.6 KB]
firststart.png [226.3 KB]
流水线式混合方法.jpeg [65.4 KB]
recommend3.png [218.1 KB]
Rocchio-2.jpg [23.7 KB]
userprofile1.jpeg [33.2 KB]
similarity_calc6.png [56.5 KB]
lambda7.png [225.2 KB]
决策树.jpg [227.4 KB]
usercf2.png [22.2 KB]
spark01.PNG [18.5 KB]
algorithm5.png [187.2 KB]
并行式-混杂式.jpeg [120.8 KB]
用户画像2.jpg [45.0 KB]
流水线式-级联式.jpeg [122.8 KB]
similarity_calc5.png [241.9 KB]
firststart2.png [564.2 KB]
itemcf1.png [103.4 KB]
usercf1.png [71.8 KB]
od2.png [4.0 KB]
user-itemMatrix4.png [51.1 KB]
usercf3.png [4.5 KB]
lambda5.png [58.1 KB]
整体式-特征组合.jpeg [105.2 KB]
混合推荐方法.jpeg [142.4 KB]
algorithm2.png [146.7 KB]
knn2.png [56.7 KB]
algorithm3.png [94.8 KB]
similarity_calc13.png [55.6 KB]
修正的余弦相似度公式.jpg [51.8 KB]
algorithm1.png [146.7 KB]
recommend4.png [103.7 KB]
itemcf2.png [113.8 KB]
recommend1.png [501.9 KB]
similarity_calc4.png [73.9 KB]
流水线式-层叠式.jpeg [124.1 KB]
整体式-特征补充.jpeg [135.1 KB]
Pearson相关系数公式.jpg [29.0 KB]
并行式混合方法.jpeg [88.8 KB]
recommend6.png [36.7 KB]
lambda4.png [97.0 KB]
user-itemMatrix.png [24.9 KB]
similarity_calc2.png [255.8 KB]
similarity_calc16.png [26.8 KB]
推荐系统.md [216.0 KB]
11_实时推荐.md [11.7 KB]
09_逻辑回归实现CTR预估.md [66.9 KB]
06_个性化电商广告推荐系统介绍.md [6.1 KB]
04_推荐算法.md [12.9 KB]
10_离线推荐处理.md [9.6 KB]
离线推荐处理.md [12.1 KB]
02_ 推荐系统评估.md [3.2 KB]
05_ 推荐系统冷启动问题.md [1.5 KB]
03_推荐系统架构设计.md [2.0 KB]
07_根据用户行为数据创建ALS模型并召回商品.md [26.0 KB]
推荐算法.md [12.7 KB]
01_推荐系统简介.md [3.7 KB]
08_CTR预估数据准备.md [71.9 KB]
📁 day16
📁 img
hbase13_2.png [13.1 KB]
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table2.png [76.7 KB]
hbase8.png [4.5 KB]
hbase11.png [172.1 KB]
cap.jpg [8.8 KB]
hbase7.png [10.3 KB]
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1542868466073.png [296.9 KB]
hbase6.png [13.1 KB]
1.png [119.1 KB]
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table1.png [54.0 KB]
table3.png [29.3 KB]
hbase10.png [261.4 KB]
hbase4.png [53.1 KB]
hbase&hive.png [93.5 KB]
2017-12-27_192757.jpg [27.7 KB]
2.png [65.7 KB]
1542868506661.png [299.8 KB]
hbase9.png [45.0 KB]
spark-hadoop2.png [110.9 KB]
2017-12-27_230552.jpg [44.8 KB]
phoenix.png [106.3 KB]
hbase14.png [36.2 KB]
2012121416.jpeg [52.9 KB]
hbase9_2.png [14.4 KB]
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structure.jpg [102.0 KB]
2017-12-27_180706.jpg [102.0 KB]
2017-12-27_173407.jpg [113.7 KB]
3.png [71.0 KB]
hbase13.png [61.5 KB]
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1542868458080.png [296.9 KB]
hbase5.png [72.1 KB]
hbase12.png [170.8 KB]
2017-12-27_230420.jpg [67.8 KB]
📁 code
hbasemanager.py [1.1 KB]
happybase_demo.py [3.4 KB]
HBase.md [39.1 KB]
h7.md [9.2 KB]
h2.md [6.9 KB]
h0.md
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h4.md [6.7 KB]
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h5.md [1.4 KB]
h6.md [9.5 KB]
h1.md [2.4 KB]
📁 day17
📁 img
dist10.png [7.1 KB]
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dist1.png [141.7 KB]
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zk1.png [441.7 KB]
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zk3.png [26.2 KB]
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dist3.png [13.5 KB]
sm02.png [127.4 KB]
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dist4.png [6.2 KB]
zk2.png [34.3 KB]
sm03.png [124.4 KB]
dist8.png [12.3 KB]
dist2.png [79.3 KB]
dist5.png [5.3 KB]
dist7.png [10.9 KB]
streaming1.png [50.8 KB]
1.png [16.1 KB]
12_python操作storm.md [2.2 KB]
07_Zookeeper选举模式和伪分布式集群搭建.md [1.8 KB]
01_Zookeeper简介.md [6.0 KB]
11_storm核心概念.md [1.8 KB]
06_Zookeeper四字命令.md [4.2 KB]
03_Zookeeper基本数据模型.md [3.3 KB]
04_Zookeeper命令行.md [9.2 KB]
10_storm入门.md [5.1 KB]
09_kazoo操作zookeeper.md [1.5 KB]
08_Zookeeper应用举例.md [416.0 B]
02_Zookeeper安装.md [1.9 KB]
05_Zookeeper_ACL权限.md [7.3 KB]
📁 day13
📁 img
error.png [36.4 KB]
hive.png [164.3 KB]
hive2.jpg [144.8 KB]
mysql.PNG [34.6 KB]
sqoop.png [119.4 KB]
hive.jpg [6.9 KB]
hive3.png [33.6 KB]
📁 code
udaf.py [993.0 B]
udaf.sh [175.0 B]
udf.py [168.0 B]
udf.sql [4.2 KB]
hive6.md [4.1 KB]
hive4.md [1.7 KB]
hive7.md [10.2 KB]
hive1.md [4.4 KB]
hive3.md [1.9 KB]
hive8.md [3.4 KB]
hive5.md [2.9 KB]
hive2.md [3.2 KB]
📁 _book
📁 day16
📁 img
2017-12-27_180515.jpg [35.2 KB]
2017-12-27_230420.jpg [67.8 KB]
cap.jpg [8.8 KB]
1542868466073.png [296.9 KB]
hbase12.png [170.8 KB]
hbase9_2.png [14.4 KB]
2.png [65.7 KB]
2017-12-27_192040.jpg [32.1 KB]
2017-12-27_173407.jpg [113.7 KB]
hbase4.png [53.1 KB]
hbase14.png [36.2 KB]
structure.jpg [102.0 KB]
1.png [119.1 KB]
phoenix.png [106.3 KB]
hbase8.png [4.5 KB]
hbase13_2.png [13.1 KB]
Consistency.png [5.7 KB]
table3.png [29.3 KB]
spark-hadoop2.png [110.9 KB]
2017-12-27_180706.jpg [102.0 KB]
2017-12-27_192757.jpg [27.7 KB]
hbase5.png [72.1 KB]
table1.png [54.0 KB]
hbase6_2.png [4.3 KB]
2012121416.jpeg [52.9 KB]
hbase13.png [61.5 KB]
hbase6.png [13.1 KB]
hbase10.png [261.4 KB]
2017-12-27_230552.jpg [44.8 KB]
1542868506661.png [299.8 KB]
hbase7.png [10.3 KB]
hbase11.png [172.1 KB]
1542868458080.png [296.9 KB]
2017-12-27_231532.jpg [47.5 KB]
3.png [71.0 KB]
hbase&hive.png [93.5 KB]
hbase9.png [45.0 KB]
table2.png [76.7 KB]
📁 code
happybase_demo.py [3.4 KB]
hbasemanager.py [1.1 KB]
h2.html [41.8 KB]
h7.html [46.9 KB]
h5.md [1.4 KB]
h4.md [6.7 KB]
h8.md [1.4 KB]
h1.html [32.0 KB]
HBase.md [39.1 KB]
h0.md
h7.md [9.2 KB]
h1.md [2.4 KB]
h3.md [3.0 KB]
h6.html [47.2 KB]
h3.html [32.6 KB]
h5.html [29.3 KB]
h4.html [40.5 KB]
h2.md [6.9 KB]
h6.md [9.5 KB]
h8.html [31.7 KB]
📁 day17
📁 img
sm03.png [124.4 KB]
streaming2.png [19.9 KB]
dist9.png [4.5 KB]
dist6.png [8.1 KB]
zk4.png [38.8 KB]
zk2.png [34.3 KB]
dist11.png [5.7 KB]
dist10.png [7.1 KB]
zk5.png [54.8 KB]
dist4.png [6.2 KB]
dist12.png [5.7 KB]
1.png [16.1 KB]
zk3.png [26.2 KB]
dist3.png [13.5 KB]
dist1.png [141.7 KB]
dist5.png [5.3 KB]
sm02.png [127.4 KB]
dist8.png [12.3 KB]
zk1.png [441.7 KB]
dist2.png [79.3 KB]
zkshell1.png [56.5 KB]
streaming1.png [50.8 KB]
dist7.png [10.9 KB]
05_Zookeeper_ACL权限.md [7.3 KB]
01_Zookeeper简介.md [6.0 KB]
04_Zookeeper命令行.md [9.2 KB]
07_Zookeeper选举模式和伪分布式集群搭建.html [29.8 KB]
02_Zookeeper安装.md [1.9 KB]
08_Zookeeper应用举例.md [416.0 B]
12_python操作storm.html [29.4 KB]
03_Zookeeper基本数据模型.md [3.3 KB]
03_Zookeeper基本数据模型.html [30.7 KB]
07_Zookeeper选举模式和伪分布式集群搭建.md [1.8 KB]
10_storm入门.md [5.1 KB]
09_kazoo操作zookeeper.html [30.0 KB]
06_Zookeeper四字命令.html [31.1 KB]
09_kazoo操作zookeeper.md [1.5 KB]
04_Zookeeper命令行.html [38.4 KB]
06_Zookeeper四字命令.md [4.2 KB]
02_Zookeeper安装.html [29.6 KB]
11_storm核心概念.html [30.2 KB]
10_storm入门.html [35.6 KB]
12_python操作storm.md [2.2 KB]
11_storm核心概念.md [1.8 KB]
01_Zookeeper简介.html [42.6 KB]
05_Zookeeper_ACL权限.html [36.0 KB]
08_Zookeeper应用举例.html [27.3 KB]
📁 gitbook
📁 gitbook-plugin-livereload
plugin.js [327.0 B]
📁 gitbook-plugin-sharing
buttons.js [2.8 KB]
📁 gitbook-plugin-search
lunr.min.js [14.7 KB]
search-engine.js [1.2 KB]
search.js [6.2 KB]
search.css [974.0 B]
📁 images
favicon.ico [4.2 KB]
apple-touch-icon-precomposed-152.png [4.7 KB]
📁 fonts
📁 fontawesome
fontawesome-webfont.woff2 [70.2 KB]
fontawesome-webfont.eot [74.7 KB]
fontawesome-webfont.woff [88.3 KB]
fontawesome-webfont.svg [382.4 KB]
FontAwesome.otf [122.1 KB]
fontawesome-webfont.ttf [149.2 KB]
📁 gitbook-plugin-lunr
lunr.min.js [14.7 KB]
search-lunr.js [1.6 KB]
📁 gitbook-plugin-fontsettings
fontsettings.js [6.3 KB]
website.css [8.4 KB]
📁 gitbook-plugin-highlight
website.css [30.7 KB]
ebook.css [2.8 KB]
theme.js [110.6 KB]
style.css [51.5 KB]
gitbook.js [102.9 KB]
📁 day13
📁 img
hive3.png [33.6 KB]
error.png [36.4 KB]
hive2.jpg [144.8 KB]
hive.jpg [6.9 KB]
hive.png [164.3 KB]
sqoop.png [119.4 KB]
mysql.PNG [34.6 KB]
📁 code
udaf.sh [175.0 B]
udaf.py [993.0 B]
udf.sql [4.2 KB]
udf.py [168.0 B]
hive3.md [1.9 KB]
hive3.html [29.8 KB]
hive8.md [3.4 KB]
hive7.html [47.2 KB]
hive8.html [34.3 KB]
hive6.html [34.5 KB]
hive2.html [31.0 KB]
hive5.md [2.9 KB]
hive4.html [29.7 KB]
hive4.md [1.7 KB]
hive2.md [3.2 KB]
hive1.md [4.4 KB]
hive1.html [35.8 KB]
hive6.md [4.1 KB]
hive7.md [10.2 KB]
hive5.html [33.0 KB]
📁 day14_15
📁 img
word2vec1.png [32.6 KB]
recommend2.png [145.1 KB]
1545630559725.png [104.3 KB]
recommend1.png [321.1 KB]
word2vec3.png [38.8 KB]
chrome_start.png [3.7 KB]
word2vec2.png [34.4 KB]
1545630651922.png [88.0 KB]
chapter9.md [10.2 KB]
chapter7.md [26.7 KB]
chapter4.md [50.9 KB]
chapter1.md [1.9 KB]
chapter5.md [9.3 KB]
chapter1.html [32.0 KB]
chapter3.md [63.9 KB]
chapter2.html [74.3 KB]
chapter10.md [8.6 KB]
chapter8.md [20.7 KB]
chapter8.html [60.5 KB]
chapter7.html [72.2 KB]
chapter4.html [125.8 KB]
chapter3.html [127.3 KB]
chapter6.html [51.3 KB]
chapter5.html [40.8 KB]
chapter10.html [45.3 KB]
chapter2.md [32.9 KB]
chapter6.md [13.1 KB]
chapter9.html [52.1 KB]
📁 day11_12
📁 img
lambda2.png [199.9 KB]
用户画像2.jpg [45.0 KB]
RS基础技术架构.png [1.1 MB]
algorithm5.png [187.2 KB]
CF介绍.png [178.0 KB]
algorithm3.png [94.8 KB]
als1.png [183.0 KB]
隐因子模型介绍.jpg [158.2 KB]
algorithm4.png [101.5 KB]
similarity_calc12.png [104.2 KB]
itemcf1.png [103.4 KB]
并行式-加权式.jpeg [129.9 KB]
algorithm2.png [146.7 KB]
algorithm1.png [146.7 KB]
RS基础业务架构.png [343.2 KB]
混合推荐方法.jpeg [142.4 KB]
lambda5.png [58.1 KB]
协同推荐评分数据集.jpg [65.8 KB]
knn2.png [56.7 KB]
Pearson相关系数公式.jpg [29.0 KB]
algorithm6.png [238.0 KB]
推荐知识库示例.jpeg [160.7 KB]
firststart2.png [564.2 KB]
1545049355235.png [86.6 KB]
similarity_calc2.png [255.8 KB]
并行式-切换式.jpeg [153.7 KB]
graph1.png [57.8 KB]
similarity_calc15.png [24.1 KB]
recommend6.png [36.7 KB]
usercf1.png [71.8 KB]
并行式混合方法.jpeg [88.8 KB]
recommend3.png [218.1 KB]
similarity_calc1.png [21.5 KB]
整体式-特征组合.jpeg [105.2 KB]
similarity_calc16.png [26.8 KB]
基础CB推荐算法.jpg [18.2 KB]
lambda4.png [97.0 KB]
similarity_calc3.png [78.0 KB]
similarity_calc11.png [64.4 KB]
并行式-混杂式.jpeg [120.8 KB]
user-itemMatrix4.png [51.1 KB]
firststart1.png [537.2 KB]
algorithm7.png [308.0 KB]
Rocchio-3.jpg [28.6 KB]
od2.png [4.0 KB]
推荐流程.png [16.9 KB]
lambda7.png [225.2 KB]
相似度计算示例.png [23.9 KB]
recommend1.png [501.9 KB]
lambda1.png [136.6 KB]
流水线式混合方法.jpeg [65.4 KB]
recommend7.jpeg [13.1 KB]
整体式-特征混合.jpeg [105.2 KB]
基于物品的预测公式.jpg [22.5 KB]
similarity_calc10.png [64.9 KB]
spark02.PNG [25.1 KB]
基于用户的预测公式.jpg [18.6 KB]
similarity_calc9.png [56.7 KB]
整体式混合方法.jpeg [103.6 KB]
similarity_calc5.png [241.9 KB]
usercf2.png [22.2 KB]
lambda6.png [85.4 KB]
recommend2.png [61.4 KB]
决策树.jpg [227.4 KB]
流水线式-级联式.jpeg [122.8 KB]
Rocchio-1.jpg [18.5 KB]
recommend4.png [103.7 KB]
整体式-特征补充.jpeg [135.1 KB]
修正的余弦相似度公式.jpg [51.8 KB]
recommend5.png [250.6 KB]
itemcf2.png [113.8 KB]
lambda3.png [167.0 KB]
knn1.png [63.8 KB]
od.png [10.6 KB]
user-itemMatrix3.png [37.9 KB]
firststart.png [226.3 KB]
usercf3.png [4.5 KB]
similarity_calc7.png [27.7 KB]
similarity_calc14.png [24.5 KB]
similarity_calc13.png [55.6 KB]
userprofile1.jpeg [33.2 KB]
流水线式-层叠式.jpeg [124.1 KB]
spark01.PNG [18.5 KB]
similarity_calc4.png [73.9 KB]
similarity_calc8.png [42.6 KB]
similarity_calc6.png [56.5 KB]
user-itemMatrix.png [24.9 KB]
Rocchio-2.jpg [23.7 KB]
挖掘频繁项集.png [102.8 KB]
user-itemMatrix2.png [86.2 KB]
02_ 推荐系统评估.md [3.2 KB]
04_推荐算法.html [57.6 KB]
推荐系统.md [216.0 KB]
05_ 推荐系统冷启动问题.md [1.5 KB]
08_CTR预估数据准备.md [71.9 KB]
09_逻辑回归实现CTR预估.md [66.9 KB]
01_推荐系统简介.md [3.7 KB]
02_ 推荐系统评估.html [33.2 KB]
07_根据用户行为数据创建ALS模型并召回商品.html [78.2 KB]
01_推荐系统简介.html [36.4 KB]
推荐算法.md [12.7 KB]
04_推荐算法.md [12.9 KB]
08_CTR预估数据准备.html [129.2 KB]
11_实时推荐.md [11.7 KB]
06_个性化电商广告推荐系统介绍.md [6.1 KB]
06_个性化电商广告推荐系统介绍.html [40.5 KB]
07_根据用户行为数据创建ALS模型并召回商品.md [26.0 KB]
05_ 推荐系统冷启动问题.html [29.8 KB]
11_实时推荐.html [44.1 KB]
10_离线推荐处理.html [46.8 KB]
10_离线推荐处理.md [9.6 KB]
09_逻辑回归实现CTR预估.html [125.2 KB]
03_推荐系统架构设计.md [2.0 KB]
离线推荐处理.md [12.1 KB]
03_推荐系统架构设计.html [30.4 KB]
search_index.json [4.0 MB]
index.html [28.0 KB]
📁 day14_15
📁 img
word2vec2.png [34.4 KB]
1545630559725.png [104.3 KB]
recommend2.png [145.1 KB]
recommend1.png [321.1 KB]
chrome_start.png [3.7 KB]
word2vec1.png [32.6 KB]
1545630651922.png [88.0 KB]
word2vec3.png [38.8 KB]
chapter9.md [10.2 KB]
chapter3.md [63.9 KB]
chapter10.md [8.6 KB]
chapter8.md [20.7 KB]
chapter5.md [9.3 KB]
chapter1.md [1.9 KB]
chapter6.md [13.1 KB]
chapter4.md [50.9 KB]
chapter2.md [32.9 KB]
chapter7.md [26.7 KB]
README.md [253.0 B]
SUMMARY.md [3.3 KB]
项目.xmind [106.2 KB]
推荐系统资料-详细.zip [152.8 MB]
📁 day07
📁 视频
10，异常值处理_.mp4 [29.6 MB]
9，缺失值处理_.mp4 [74.3 MB]
16，数据集介绍_.mp4 [64.8 MB]
15，状态操作-windows_.mp4 [48.1 MB]
12，SparkStreaming的组件_.mp4 [14.8 MB]
7，上午小结_.mp4 [16.2 MB]
3，创建DataFrame的一些方法_.mp4 [59.8 MB]
1，回顾_.mp4 [45.0 MB]
4，Spark的DataFrame api_.mp4 [90.5 MB]
14，状态操作-updateStateByKey_.mp4 [46.2 MB]
6，动态json数据的读取和操作_.mp4 [30.7 MB]
8，数据去重_.mp4 [11.1 MB]
2，SparkSQL介绍_.mp4 [64.2 MB]
5，静态json数据的读取和操作_.mp4 [29.9 MB]
17，总结_.mp4 [254.6 MB]
13，SparkStreaming实现WordCount_.mp4 [31.5 MB]
11，SparkStreaming介绍_.mp4 [28.0 MB]
📁 资料
项目.xmind [64.0 KB]
SparkStreaming.xmind [63.9 KB]
user_profile.csv [22.9 MB]
SparkSQL.xmind [89.3 KB]
ad_feature.csv [29.8 MB]
Spark-core.xmind [152.2 KB]
raw_sample.csv [1.0 GB]
📁 day04
📁 资料
📁 day11-day17
📁 day13
📁 img
hive.png [164.3 KB]
sqoop.png [119.4 KB]
hive.jpg [6.9 KB]
error.png [36.4 KB]
hive2.jpg [144.8 KB]
mysql.PNG [34.6 KB]
hive3.png [33.6 KB]
📁 code
udf.py [168.0 B]
udaf.sh [175.0 B]
udf.sql [4.2 KB]
udaf.py [993.0 B]
hive2.md [3.2 KB]
hive3.md [1.9 KB]
hive7.md [10.2 KB]
hive4.md [1.7 KB]
hive5.md [2.9 KB]
hive6.md [4.1 KB]
hive1.md [4.4 KB]
hive8.md [3.4 KB]
📁 day14_15
📁 img
1545630651922.png [88.0 KB]
chrome_start.png [3.7 KB]
word2vec3.png [38.8 KB]
word2vec1.png [32.6 KB]
word2vec2.png [34.4 KB]
1545630559725.png [104.3 KB]
recommend1.png [321.1 KB]
recommend2.png [145.1 KB]
chapter2.md [32.9 KB]
chapter4.md [50.9 KB]
chapter1.md [1.9 KB]
chapter7.md [26.7 KB]
chapter3.md [63.9 KB]
chapter5.md [9.3 KB]
chapter6.md [13.1 KB]
chapter9.md [10.2 KB]
chapter10.md [8.6 KB]
chapter8.md [20.7 KB]
📁 day16
📁 img
hbase4.png [53.1 KB]
spark-hadoop2.png [110.9 KB]
hbase11.png [172.1 KB]
hbase5.png [72.1 KB]
2017-12-27_180515.jpg [35.2 KB]
2017-12-27_231532.jpg [47.5 KB]
2017-12-27_173407.jpg [113.7 KB]
hbase&hive.png [93.5 KB]
hbase12.png [170.8 KB]
hbase8.png [4.5 KB]
hbase10.png [261.4 KB]
hbase13_2.png [13.1 KB]
table1.png [54.0 KB]
cap.jpg [8.8 KB]
1.png [119.1 KB]
2017-12-27_230420.jpg [67.8 KB]
hbase6_2.png [4.3 KB]
2017-12-27_180706.jpg [102.0 KB]
2012121416.jpeg [52.9 KB]
hbase13.png [61.5 KB]
1542868458080.png [296.9 KB]
structure.jpg [102.0 KB]
phoenix.png [106.3 KB]
2017-12-27_192040.jpg [32.1 KB]
table3.png [29.3 KB]
2017-12-27_192757.jpg [27.7 KB]
hbase6.png [13.1 KB]
table2.png [76.7 KB]
1542868506661.png [299.8 KB]
2017-12-27_230552.jpg [44.8 KB]
3.png [71.0 KB]
hbase14.png [36.2 KB]
2.png [65.7 KB]
hbase9.png [45.0 KB]
Consistency.png [5.7 KB]
hbase7.png [10.3 KB]
hbase9_2.png [14.4 KB]
1542868466073.png [296.9 KB]
📁 code
happybase_demo.py [3.4 KB]
hbasemanager.py [1.1 KB]
h6.md [9.5 KB]
h2.md [6.9 KB]
h0.md
h3.md [3.0 KB]
h7.md [9.2 KB]
h8.md [1.4 KB]
h5.md [1.4 KB]
HBase.md [39.1 KB]
h4.md [6.7 KB]
h1.md [2.4 KB]
📁 day11_12
📁 img
algorithm3.png [94.8 KB]
基于用户的预测公式.jpg [18.6 KB]
决策树.jpg [227.4 KB]
od.png [10.6 KB]
Rocchio-2.jpg [23.7 KB]
Rocchio-3.jpg [28.6 KB]
spark01.PNG [18.5 KB]
流水线式混合方法.jpeg [65.4 KB]
整体式-特征组合.jpeg [105.2 KB]
firststart2.png [564.2 KB]
similarity_calc10.png [64.9 KB]
similarity_calc2.png [255.8 KB]
itemcf1.png [103.4 KB]
graph1.png [57.8 KB]
als1.png [183.0 KB]
recommend2.png [61.4 KB]
similarity_calc12.png [104.2 KB]
挖掘频繁项集.png [102.8 KB]
推荐知识库示例.jpeg [160.7 KB]
lambda3.png [167.0 KB]
similarity_calc7.png [27.7 KB]
similarity_calc11.png [64.4 KB]
similarity_calc13.png [55.6 KB]
隐因子模型介绍.jpg [158.2 KB]
协同推荐评分数据集.jpg [65.8 KB]
整体式混合方法.jpeg [103.6 KB]
algorithm5.png [187.2 KB]
RS基础业务架构.png [343.2 KB]
混合推荐方法.jpeg [142.4 KB]
并行式-切换式.jpeg [153.7 KB]
recommend4.png [103.7 KB]
lambda1.png [136.6 KB]
firststart1.png [537.2 KB]
knn1.png [63.8 KB]
algorithm7.png [308.0 KB]
流水线式-层叠式.jpeg [124.1 KB]
algorithm4.png [101.5 KB]
CF介绍.png [178.0 KB]
修正的余弦相似度公式.jpg [51.8 KB]
algorithm2.png [146.7 KB]
user-itemMatrix4.png [51.1 KB]
similarity_calc16.png [26.8 KB]
整体式-特征混合.jpeg [105.2 KB]
similarity_calc1.png [21.5 KB]
similarity_calc8.png [42.6 KB]
lambda7.png [225.2 KB]
并行式混合方法.jpeg [88.8 KB]
recommend5.png [250.6 KB]
整体式-特征补充.jpeg [135.1 KB]
algorithm1.png [146.7 KB]
firststart.png [226.3 KB]
userprofile1.jpeg [33.2 KB]
usercf3.png [4.5 KB]
并行式-混杂式.jpeg [120.8 KB]
algorithm6.png [238.0 KB]
lambda4.png [97.0 KB]
流水线式-级联式.jpeg [122.8 KB]
RS基础技术架构.png [1.1 MB]
相似度计算示例.png [23.9 KB]
user-itemMatrix.png [24.9 KB]
itemcf2.png [113.8 KB]
similarity_calc6.png [56.5 KB]
并行式-加权式.jpeg [129.9 KB]
similarity_calc15.png [24.1 KB]
Rocchio-1.jpg [18.5 KB]
similarity_calc4.png [73.9 KB]
基于物品的预测公式.jpg [22.5 KB]
user-itemMatrix3.png [37.9 KB]
lambda5.png [58.1 KB]
recommend7.jpeg [13.1 KB]
usercf2.png [22.2 KB]
recommend3.png [218.1 KB]
similarity_calc3.png [78.0 KB]
similarity_calc9.png [56.7 KB]
recommend6.png [36.7 KB]
lambda6.png [85.4 KB]
lambda2.png [199.9 KB]
usercf1.png [71.8 KB]
knn2.png [56.7 KB]
od2.png [4.0 KB]
spark02.PNG [25.1 KB]
Pearson相关系数公式.jpg [29.0 KB]
user-itemMatrix2.png [86.2 KB]
recommend1.png [501.9 KB]
基础CB推荐算法.jpg [18.2 KB]
similarity_calc5.png [241.9 KB]
推荐流程.png [16.9 KB]
用户画像2.jpg [45.0 KB]
1545049355235(1).png [86.6 KB]
similarity_calc14.png [24.5 KB]
推荐算法.md [12.7 KB]
离线推荐处理.md [12.1 KB]
11_实时推荐.md [11.7 KB]
01_推荐系统简介.md [3.7 KB]
推荐系统.md [216.0 KB]
07_根据用户行为数据创建ALS模型并召回商品.md [26.0 KB]
08_CTR预估数据准备.md [71.9 KB]
03_推荐系统架构设计.md [2.0 KB]
09_逻辑回归实现CTR预估.md [66.9 KB]
10_离线推荐处理.md [9.6 KB]
04_推荐算法.md [12.9 KB]
02_ 推荐系统评估.md [3.2 KB]
06_个性化电商广告推荐系统介绍.md [6.1 KB]
05_ 推荐系统冷启动问题.md [1.5 KB]
📁 _book
📁 day17
📁 img
dist1.png [141.7 KB]
dist7.png [10.9 KB]
zk2.png [34.3 KB]
dist4.png [6.2 KB]
dist10.png [7.1 KB]
zk5.png [54.8 KB]
dist11.png [5.7 KB]
dist8.png [12.3 KB]
dist2.png [79.3 KB]
dist12.png [5.7 KB]
zk1.png [441.7 KB]
sm02.png [127.4 KB]
dist6.png [8.1 KB]
zkshell1.png [56.5 KB]
streaming1.png [50.8 KB]
dist9.png [4.5 KB]
zk3.png [26.2 KB]
sm03.png [124.4 KB]
dist5.png [5.3 KB]
streaming2.png [19.9 KB]
1.png [16.1 KB]
dist3.png [13.5 KB]
zk4.png [38.8 KB]
08_Zookeeper应用举例.html [27.3 KB]
02_Zookeeper安装.html [29.6 KB]
03_Zookeeper基本数据模型.html [30.7 KB]
03_Zookeeper基本数据模型.md [3.3 KB]
05_Zookeeper_ACL权限.md [7.3 KB]
08_Zookeeper应用举例.md [416.0 B]
07_Zookeeper选举模式和伪分布式集群搭建.html [29.8 KB]
12_python操作storm.md [2.2 KB]
07_Zookeeper选举模式和伪分布式集群搭建.md [1.8 KB]
04_Zookeeper命令行.html [38.4 KB]
10_storm入门.md [5.1 KB]
06_Zookeeper四字命令.html [31.1 KB]
12_python操作storm.html [29.4 KB]
11_storm核心概念.html [30.2 KB]
09_kazoo操作zookeeper.md [1.5 KB]
06_Zookeeper四字命令.md [4.2 KB]
02_Zookeeper安装.md [1.9 KB]
05_Zookeeper_ACL权限.html [36.0 KB]
01_Zookeeper简介.html [42.6 KB]
09_kazoo操作zookeeper.html [30.0 KB]
01_Zookeeper简介.md [6.0 KB]
11_storm核心概念.md [1.8 KB]
10_storm入门.html [35.6 KB]
04_Zookeeper命令行.md [9.2 KB]
📁 gitbook
📁 gitbook-plugin-highlight
website.css [30.7 KB]
ebook.css [2.8 KB]
📁 gitbook-plugin-search
lunr.min.js [14.7 KB]
search-engine.js [1.2 KB]
search.css [974.0 B]
search.js [6.2 KB]
📁 gitbook-plugin-fontsettings
website.css [8.4 KB]
fontsettings.js [6.3 KB]
📁 gitbook-plugin-lunr
lunr.min.js [14.7 KB]
search-lunr.js [1.6 KB]
📁 images
favicon.ico [4.2 KB]
apple-touch-icon-precomposed-152.png [4.7 KB]
📁 gitbook-plugin-sharing
buttons.js [2.8 KB]
📁 fonts
📁 fontawesome
fontawesome-webfont.woff2 [70.2 KB]
fontawesome-webfont.eot [74.7 KB]
fontawesome-webfont.woff [88.3 KB]
fontawesome-webfont.svg [382.4 KB]
fontawesome-webfont.ttf [149.2 KB]
FontAwesome.otf [122.1 KB]
📁 gitbook-plugin-livereload
plugin.js [327.0 B]
gitbook.js [102.9 KB]
style.css [51.5 KB]
theme.js [110.6 KB]
📁 day13
📁 img
error.png [36.4 KB]
sqoop.png [119.4 KB]
hive.jpg [6.9 KB]
hive2.jpg [144.8 KB]
hive3.png [33.6 KB]
mysql.PNG [34.6 KB]
hive.png [164.3 KB]
📁 code
udaf.py [993.0 B]
udf.py [168.0 B]
udaf.sh [175.0 B]
udf.sql [4.2 KB]
hive8.html [34.3 KB]
hive8.md [3.4 KB]
hive7.md [10.2 KB]
hive2.html [31.0 KB]
hive1.html [35.8 KB]
hive6.html [34.5 KB]
hive5.md [2.9 KB]
hive5.html [33.0 KB]
hive6.md [4.1 KB]
hive2.md [3.2 KB]
hive4.html [29.7 KB]
hive1.md [4.4 KB]
hive3.md [1.9 KB]
hive3.html [29.8 KB]
hive4.md [1.7 KB]
hive7.html [47.2 KB]
📁 day11_12
📁 img
lambda2.png [199.9 KB]
recommend6.png [36.7 KB]
similarity_calc3.png [78.0 KB]
基于物品的预测公式.jpg [22.5 KB]
usercf2.png [22.2 KB]
algorithm7.png [308.0 KB]
od2.png [4.0 KB]
user-itemMatrix4.png [51.1 KB]
隐因子模型介绍.jpg [158.2 KB]
Rocchio-1.jpg [18.5 KB]
recommend5.png [250.6 KB]
knn1.png [63.8 KB]
userprofile1.jpeg [33.2 KB]
lambda5.png [58.1 KB]
similarity_calc14.png [24.5 KB]
CF介绍.png [178.0 KB]
itemcf2.png [113.8 KB]
Rocchio-2.jpg [23.7 KB]
similarity_calc16.png [26.8 KB]
并行式混合方法.jpeg [88.8 KB]
lambda3.png [167.0 KB]
修正的余弦相似度公式.jpg [51.8 KB]
similarity_calc12.png [104.2 KB]
firststart.png [226.3 KB]
推荐知识库示例.jpeg [160.7 KB]
推荐流程.png [16.9 KB]
混合推荐方法.jpeg [142.4 KB]
recommend3.png [218.1 KB]
similarity_calc13.png [55.6 KB]
基础CB推荐算法.jpg [18.2 KB]
user-itemMatrix3.png [37.9 KB]
spark01.PNG [18.5 KB]
并行式-加权式.jpeg [129.9 KB]
itemcf1.png [103.4 KB]
相似度计算示例.png [23.9 KB]
RS基础业务架构.png [343.2 KB]
整体式-特征混合.jpeg [105.2 KB]
lambda4.png [97.0 KB]
recommend2.png [61.4 KB]
user-itemMatrix.png [24.9 KB]
usercf3.png [4.5 KB]
similarity_calc7.png [27.7 KB]
similarity_calc11.png [64.4 KB]
usercf1.png [71.8 KB]
knn2.png [56.7 KB]
1545049355235.png [86.6 KB]
similarity_calc1.png [21.5 KB]
algorithm5.png [187.2 KB]
RS基础技术架构.png [1.1 MB]
recommend7.jpeg [13.1 KB]
Pearson相关系数公式.jpg [29.0 KB]
als1.png [183.0 KB]
流水线式-级联式.jpeg [122.8 KB]
spark02.PNG [25.1 KB]
Rocchio-3.jpg [28.6 KB]
similarity_calc9.png [56.7 KB]
用户画像2.jpg [45.0 KB]
lambda7.png [225.2 KB]
algorithm2(1).png [146.7 KB]
流水线式-层叠式.jpeg [124.1 KB]
similarity_calc8.png [42.6 KB]
similarity_calc10.png [64.9 KB]
similarity_calc15.png [24.1 KB]
user-itemMatrix2.png [86.2 KB]
整体式-特征组合.jpeg [105.2 KB]
algorithm6.png [238.0 KB]
algorithm3.png [94.8 KB]
firststart2.png [564.2 KB]
similarity_calc4.png [73.9 KB]
recommend4.png [103.7 KB]
od.png [10.6 KB]
协同推荐评分数据集.jpg [65.8 KB]
并行式-混杂式.jpeg [120.8 KB]
similarity_calc6.png [56.5 KB]
整体式混合方法.jpeg [103.6 KB]
lambda6.png [85.4 KB]
lambda1.png [136.6 KB]
流水线式混合方法.jpeg [65.4 KB]
决策树.jpg [227.4 KB]
recommend1.png [501.9 KB]
similarity_calc2.png [255.8 KB]
graph1.png [57.8 KB]
基于用户的预测公式.jpg [18.6 KB]
similarity_calc5.png [241.9 KB]
挖掘频繁项集.png [102.8 KB]
algorithm4.png [101.5 KB]
并行式-切换式.jpeg [153.7 KB]
algorithm1.png [146.7 KB]
firststart1.png [537.2 KB]
整体式-特征补充.jpeg [135.1 KB]
推荐系统.md [216.0 KB]
06_个性化电商广告推荐系统介绍.html [40.5 KB]
10_离线推荐处理.html [46.8 KB]
离线推荐处理.md [12.1 KB]
02_ 推荐系统评估.html [33.2 KB]
07_根据用户行为数据创建ALS模型并召回商品.md [26.0 KB]
06_个性化电商广告推荐系统介绍.md [6.1 KB]
11_实时推荐.html [44.1 KB]
01_推荐系统简介.md [3.7 KB]
10_离线推荐处理.md [9.6 KB]
08_CTR预估数据准备.md [71.9 KB]
04_推荐算法.html [57.6 KB]
推荐算法.md [12.7 KB]
07_根据用户行为数据创建ALS模型并召回商品.html [78.2 KB]
09_逻辑回归实现CTR预估.md [66.9 KB]
09_逻辑回归实现CTR预估.html [125.2 KB]
05_ 推荐系统冷启动问题.md [1.5 KB]
01_推荐系统简介.html [36.4 KB]
11_实时推荐.md [11.7 KB]
02_ 推荐系统评估.md [3.2 KB]
03_推荐系统架构设计.html [30.4 KB]
08_CTR预估数据准备.html [129.2 KB]
05_ 推荐系统冷启动问题.html [29.8 KB]
04_推荐算法.md [12.9 KB]
03_推荐系统架构设计.md [2.0 KB]
📁 day16
📁 code
hbasemanager.py [1.1 KB]
happybase_demo.py [3.4 KB]
📁 img
2.png [65.7 KB]
hbase11.png [172.1 KB]
1542868506661.png [299.8 KB]
2017-12-27_192757.jpg [27.7 KB]
hbase6_2.png [4.3 KB]
hbase5.png [72.1 KB]
hbase13_2.png [13.1 KB]
hbase14.png [36.2 KB]
1542868466073.png [296.9 KB]
1.png [119.1 KB]
phoenix.png [106.3 KB]
spark-hadoop2.png [110.9 KB]
2017-12-27_230552.jpg [44.8 KB]
cap.jpg [8.8 KB]
2017-12-27_180706.jpg [102.0 KB]
hbase12.png [170.8 KB]
hbase13.png [61.5 KB]
table3.png [29.3 KB]
hbase9_2.png [14.4 KB]
table1.png [54.0 KB]
2017-12-27_231532.jpg [47.5 KB]
hbase9.png [45.0 KB]
hbase&hive.png [93.5 KB]
2017-12-27_230420.jpg [67.8 KB]
hbase6.png [13.1 KB]
1542868458080.png [296.9 KB]
2017-12-27_192040.jpg [32.1 KB]
hbase8.png [4.5 KB]
hbase10.png [261.4 KB]
hbase7.png [10.3 KB]
2017-12-27_173407.jpg [113.7 KB]
table2.png [76.7 KB]
2017-12-27_180515.jpg [35.2 KB]
3.png [71.0 KB]
hbase4.png [53.1 KB]
structure.jpg [102.0 KB]
2012121416.jpeg [52.9 KB]
Consistency.png [5.7 KB]
h6.html [47.2 KB]
h6.md [9.5 KB]
h3.md [3.0 KB]
h7.html [46.9 KB]
h2.md [6.9 KB]
h3.html [32.6 KB]
HBase.md [39.1 KB]
h8.html [31.7 KB]
h4.md [6.7 KB]
h5.md [1.4 KB]
h0.md
h1.md [2.4 KB]
h2.html [41.8 KB]
h7.md [9.2 KB]
h5.html [29.3 KB]
h1.html [32.0 KB]
h4.html [40.5 KB]
h8.md [1.4 KB]
📁 day14_15
📁 img
chrome_start.png [3.7 KB]
word2vec2.png [34.4 KB]
word2vec1.png [32.6 KB]
recommend1.png [321.1 KB]
word2vec3.png [38.8 KB]
recommend2.png [145.1 KB]
1545630559725.png [104.3 KB]
1545630651922.png [88.0 KB]
chapter10.md [8.6 KB]
chapter8.html [60.5 KB]
chapter4.html [125.8 KB]
chapter9.html [52.1 KB]
chapter2.html [74.3 KB]
chapter1.md [1.9 KB]
chapter9.md [10.2 KB]
chapter3.html [127.3 KB]
chapter5.md [9.3 KB]
chapter8.md [20.7 KB]
chapter3.md [63.9 KB]
chapter7.md [26.7 KB]
chapter4.md [50.9 KB]
chapter5.html [40.8 KB]
chapter1.html [32.0 KB]
chapter2.md [32.9 KB]
chapter6.md [13.1 KB]
chapter7.html [72.2 KB]
chapter6.html [51.3 KB]
chapter10.html [45.3 KB]
index.html [28.0 KB]
search_index.json [4.0 MB]
📁 day17
📁 img
dist1.png [141.7 KB]
zk2.png [34.3 KB]
dist8.png [12.3 KB]
zk1.png [441.7 KB]
dist3.png [13.5 KB]
streaming1.png [50.8 KB]
streaming2.png [19.9 KB]
1.png [16.1 KB]
dist11.png [5.7 KB]
sm03.png [124.4 KB]
dist9.png [4.5 KB]
dist10.png [7.1 KB]
sm02.png [127.4 KB]
dist2.png [79.3 KB]
dist12.png [5.7 KB]
dist5.png [5.3 KB]
zk5.png [54.8 KB]
dist4.png [6.2 KB]
zk3.png [26.2 KB]
zkshell1.png [56.5 KB]
dist6.png [8.1 KB]
dist7.png [10.9 KB]
zk4.png [38.8 KB]
04_Zookeeper命令行.md [9.2 KB]
05_Zookeeper_ACL权限.md [7.3 KB]
10_storm入门.md [5.1 KB]
01_Zookeeper简介.md [6.0 KB]
08_Zookeeper应用举例.md [416.0 B]
11_storm核心概念.md [1.8 KB]
09_kazoo操作zookeeper.md [1.5 KB]
06_Zookeeper四字命令.md [4.2 KB]
07_Zookeeper选举模式和伪分布式集群搭建.md [1.8 KB]
12_python操作storm.md [2.2 KB]
02_Zookeeper安装.md [1.9 KB]
03_Zookeeper基本数据模型.md [3.3 KB]
SUMMARY.md [3.3 KB]
README.md [253.0 B]
📁 day05-day10
📁 day06
📁 img
📁 hdfs_read_write
g.jpg [155.1 KB]
c.jpg [135.7 KB]
a.jpg [135.6 KB]
e.jpg [156.9 KB]
j.jpg [156.4 KB]
b.jpg [138.3 KB]
k.jpg [53.1 KB]
d.jpg [137.8 KB]
i.jpg [157.6 KB]
h.jpg [156.2 KB]
yarn_architecture.gif [32.3 KB]
image-MapReduce5.png [334.6 KB]
image-bigdata01.png [546.4 KB]
image-大数据应用3.png [1008.5 KB]
zq6.png [8.5 KB]
image-大数据行业应用.png [526.8 KB]
zq13.png [148.3 KB]
image-mapreduce1.png [327.3 KB]
zq8.png [3.1 KB]
mp4.png [461.0 KB]
zq11.png [48.6 KB]
zq14.png [318.3 KB]
zq5.png [14.0 KB]
hadoop-hdfsarchitecture.png [39.6 KB]
zq3.png [86.7 KB]
mp3.png [666.8 KB]
mp1.png [991.2 KB]
hdfs_arc.png [55.9 KB]
image-大数据应用2.png [1.3 MB]
zq10.png [154.5 KB]
hadoop-生态.png [396.0 KB]
mp5.png [863.2 KB]
mr_result.png [38.1 KB]
image-mapreduce3.png [1.1 MB]
image-mapreduce2.png [668.1 KB]
zq4.png [103.3 KB]
hadoop-hdfs1.png [29.3 KB]
yarn4.png [70.9 KB]
image-yarn2.png [652.6 KB]
mp6.png [916.5 KB]
image-mapreduce.png [524.6 KB]
image-yarn.png [656.7 KB]
zq7.png [132.4 KB]
zq2.png [19.7 KB]
zq1.png [8.1 KB]
zq12.png [50.1 KB]
hadoop-yarn.jpg [34.5 KB]
image-hadoop1.png [433.1 KB]
hadoop-yarn3.png [96.4 KB]
zq9.png [260.6 KB]
image-MapReduce4.png [335.6 KB]
ha4.0.md [119.0 B]
ha3.1.md [3.6 KB]
ha3.4.md [3.3 KB]
ha4.1.md [9.4 KB]
ha3.5.md [7.9 KB]
ha4.4.md [5.3 KB]
ha4.2.md [3.3 KB]
ha4.5.md [3.5 KB]
ha4.3.md [3.2 KB]
ha3.0.md [99.0 B]
ha3.2.md [3.2 KB]
ha3.3.md [2.7 KB]
ha3.md [334.0 B]
📁 day09
📁 pics
s1.PNG [19.0 KB]
kafka_8.png [386.8 KB]
1540347254561.png [32.7 KB]
s9.PNG [292.5 KB]
kafka_15.png [56.2 KB]
1540350674304.png [21.2 KB]
1540347375394.png [52.7 KB]
kafka_3.png [83.6 KB]
kafka_10.png [238.6 KB]
kafka_17.png [129.5 KB]
s10.PNG [79.2 KB]
kafka_14.png [91.6 KB]
s2.PNG [16.6 KB]
s5.PNG [143.6 KB]
1540350201715.png [78.7 KB]
1540350245310.png [223.5 KB]
1540347422756.png [102.2 KB]
s14.PNG [128.0 KB]
s11.PNG [232.2 KB]
1540349692086.png [47.4 KB]
1540347389671.png [52.7 KB]
s7.PNG [339.4 KB]
s12.PNG [305.8 KB]
1540349678122.png [37.2 KB]
s4.PNG [286.5 KB]
kafka_6.png [60.6 KB]
宽依赖和窄依赖.png [250.5 KB]
kafka_9.png [57.1 KB]
kafka_4.png [60.6 KB]
s8.PNG [203.5 KB]
kafka_7.png [393.8 KB]
1540350260244.png [223.5 KB]
kafka_5.png [253.0 KB]
kafka_13.png [222.3 KB]
kafka_11.png [78.6 KB]
s6.PNG [102.5 KB]
s13.PNG [297.4 KB]
s3.PNG [86.2 KB]
kafka_2.png [22.7 KB]
kafka_16.png [51.2 KB]
kafka_12.png [147.0 KB]
s1.1.md [2.4 KB]
s1.0.md [186.0 B]
s1.5.md [7.2 KB]
s1.2.md [7.8 KB]
s1.4.md [20.8 KB]
s.md [84.0 B]
s1.3.md [6.5 KB]
📁 day07
📁 pics
1540350260244.png [223.5 KB]
kafka_5.png [253.0 KB]
kafka_10.png [238.6 KB]
宽依赖和窄依赖.png [250.5 KB]
f2.png [114.3 KB]
1540349692086.png [35.3 KB]
kafka_13.png [222.3 KB]
1540347389671.png [52.7 KB]
k4.PNG [18.2 KB]
kafka_14.png [91.6 KB]
f4.png [22.9 KB]
1540347375394.png [52.7 KB]
k3.PNG [65.8 KB]
1540349678122.png [32.9 KB]
kafka_12.png [147.0 KB]
1540347254561.png [32.7 KB]
f1.png [447.0 KB]
kafka_16.png [51.2 KB]
kafka_2.png [22.7 KB]
kafka_3.png [83.6 KB]
kafka_15.png [56.2 KB]
1540350674304.png [21.2 KB]
kafka_17.png [129.5 KB]
k5.PNG [58.4 KB]
kafka_4.png [60.6 KB]
kafka_7.png [393.8 KB]
kafka_9.png [57.1 KB]
f3.png [36.9 KB]
kafka_6.png [60.6 KB]
k2.PNG [22.7 KB]
1540350201715.png [78.7 KB]
kafka_8.png [386.8 KB]
1540347422756.png [102.2 KB]
kafka_11.png [78.6 KB]
k1.PNG [19.1 KB]
1540350245310.png [223.5 KB]
k1.1.md [2.5 KB]
f1.4.md [2.1 KB]
f1.2.md [3.9 KB]
f1.3.md [301.0 B]
f1.7.md [10.4 KB]
f1.6.md [6.7 KB]
k1.5.md [3.1 KB]
k1.0.md [454.0 B]
k1.2.md [4.8 KB]
k1.4.md [1.5 KB]
k.md [160.0 B]
f1.0.md [382.0 B]
k1.3.md [3.5 KB]
f1.1.md [2.5 KB]
f1.5.md [10.0 KB]
f.md [300.0 B]
📁 day08
📁 pics
kafka_3.png [83.6 KB]
宽依赖和窄依赖.png [250.5 KB]
1540349692086.png [47.4 KB]
s3.PNG [86.2 KB]
spark2.PNG [12.0 KB]
s1.PNG [19.0 KB]
kafka_4.png [60.6 KB]
1540347422756.png [102.2 KB]
s7.PNG [339.4 KB]
kafka_8.png [386.8 KB]
1540347389671.png [52.7 KB]
s4.PNG [286.5 KB]
kafka_10.png [238.6 KB]
spark1.PNG [15.4 KB]
kafka_17.png [129.5 KB]
kafka_7.png [393.8 KB]
1540350201715.png [78.7 KB]
kafka_12.png [147.0 KB]
1540349678122.png [37.2 KB]
s8.PNG [203.5 KB]
kafka_11.png [78.6 KB]
1540350674304.png [21.2 KB]
spark3.PNG [90.6 KB]
s2.PNG [16.6 KB]
1540350260244.png [223.5 KB]
kafka_15.png [56.2 KB]
kafka_5.png [253.0 KB]
kafka_13.png [222.3 KB]
s6.PNG [102.5 KB]
kafka_14.png [91.6 KB]
1540347375394.png [52.7 KB]
1540347254561.png [32.7 KB]
1540350245310.png [223.5 KB]
kafka_6.png [60.6 KB]
s5.PNG [143.6 KB]
kafka_9.png [57.1 KB]
kafka_16.png [51.2 KB]
kafka_2.png [22.7 KB]
📁 资料
access.log [2.9 MB]
20090121000132.394251.http.format [1.9 MB]
ip.txt [13.7 MB]
user.txt [150.0 B]
s.md [71.0 B]
s1.3.md [655.0 B]
s1.6.md [4.8 KB]
s1.2.md [1.4 KB]
s1.0.md [242.0 B]
s1.4.md [4.7 KB]
s1.5.md [2.7 KB]
s1.1.md [8.4 KB]
📁 _book
📁 gitbook
📁 images
favicon.ico [4.2 KB]
apple-touch-icon-precomposed-152.png [4.7 KB]
📁 gitbook-plugin-sharing
buttons.js [2.8 KB]
📁 gitbook-plugin-lunr
lunr.min.js [14.7 KB]
search-lunr.js [1.6 KB]
📁 gitbook-plugin-livereload
plugin.js [327.0 B]
📁 fonts
📁 fontawesome
FontAwesome.otf [122.1 KB]
fontawesome-webfont.ttf [149.2 KB]
fontawesome-webfont.eot [74.7 KB]
fontawesome-webfont.svg [382.4 KB]
fontawesome-webfont.woff2 [70.2 KB]
fontawesome-webfont.woff [88.3 KB]
📁 gitbook-plugin-search
search(1).js [6.2 KB]
lunr.min.js [14.7 KB]
search-engine.js [1.2 KB]
search.css [974.0 B]
📁 gitbook-plugin-fontsettings
website.css [8.4 KB]
fontsettings.js [6.3 KB]
📁 gitbook-plugin-highlight
website.css [30.7 KB]
ebook.css [2.8 KB]
gitbook.js [102.9 KB]
theme.js [110.6 KB]
style.css [51.5 KB]
📁 day05
📁 img
📁 hdfs_read_write
a.jpg [135.6 KB]
c.jpg [135.7 KB]
k.jpg [53.1 KB]
h.jpg [156.2 KB]
g.jpg [155.1 KB]
b.jpg [138.3 KB]
i.jpg [157.6 KB]
j.jpg [156.4 KB]
e.jpg [156.9 KB]
d.jpg [137.8 KB]
image-MapReduce4.png [335.6 KB]
image-yarn.png [656.7 KB]
image-yarn2.png [652.6 KB]
image-mapreduce.png [524.6 KB]
hadoop-yarn(1).jpg [34.5 KB]
hadoop-生态.png [396.0 KB]
image-大数据应用3.png [1008.5 KB]
image-MapReduce5.png [334.6 KB]
image-bigdata01.png [546.4 KB]
yarn_architecture.gif [32.3 KB]
mr_result.png [38.1 KB]
hadoop-yarn3.png [96.4 KB]
mp3.png [666.8 KB]
hdfs_arc.png [55.9 KB]
image-mapreduce1.png [327.3 KB]
mp4.png [461.0 KB]
mp5.png [863.2 KB]
mp1.png [991.2 KB]
image-大数据应用2.png [1.3 MB]
image-mapreduce2.png [668.1 KB]
hadoop-hdfs1.png [29.3 KB]
yarn4.png [70.9 KB]
image-mapreduce3.png [1.1 MB]
image-hadoop1.png [433.1 KB]
mp6.png [916.5 KB]
hadoop-hdfsarchitecture.png [39.6 KB]
image-大数据行业应用.png [526.8 KB]
ha2.0.html [29.6 KB]
ha1.4.md [950.0 B]
ha1.5.md [256.0 B]
ha2.7.html [31.2 KB]
ha1.1.html [34.0 KB]
ha2.2.html [30.1 KB]
ha1.4.html [31.4 KB]
ha2.5.html [37.9 KB]
ha2.6.md [2.1 KB]
ha2.2.md [522.0 B]
ha2.3.md [1.9 KB]
ha2.7.md [268.0 B]
ha1.3.html [29.8 KB]
ha2.5.md [4.5 KB]
ha2.1.html [30.8 KB]
ha1.2.md [1.3 KB]
ha1.0.html [31.0 KB]
ha1.5.html [30.5 KB]
ha2.3.html [32.0 KB]
ha1.2.html [31.7 KB]
ha1.3.md [324.0 B]
ha1.1.md [2.4 KB]
ha1.0.md [150.0 B]
ha2.4.md [1.9 KB]
ha2.1.md [412.0 B]
ha2.0.md [212.0 B]
ha.md [115.0 B]
ha2.4.html [33.1 KB]
ha.html [29.9 KB]
ha2.6.html [33.9 KB]
📁 day06
📁 img
📁 hdfs_read_write
e.jpg [156.9 KB]
i.jpg [157.6 KB]
g.jpg [155.1 KB]
h.jpg [156.2 KB]
k.jpg [53.1 KB]
c.jpg [135.7 KB]
b.jpg [138.3 KB]
j.jpg [156.4 KB]
a.jpg [135.6 KB]
d.jpg [137.8 KB]
zq11.png [48.6 KB]
image-yarn.png [656.7 KB]
hdfs_arc.png [55.9 KB]
zq1.png [8.1 KB]
image-mapreduce2.png [668.1 KB]
zq8.png [3.1 KB]
zq3.png [86.7 KB]
hadoop-yarn.jpg [34.5 KB]
hadoop-yarn3.png [96.4 KB]
hadoop-hdfsarchitecture.png [39.6 KB]
image-MapReduce5.png [334.6 KB]
image-大数据应用2.png [1.3 MB]
image-yarn2.png [652.6 KB]
zq12.png [50.1 KB]
zq5.png [14.0 KB]
mr_result.png [38.1 KB]
image-MapReduce4.png [335.6 KB]
image-mapreduce3.png [1.1 MB]
image-大数据应用3.png [1008.5 KB]
hadoop-生态.png [396.0 KB]
zq7.png [132.4 KB]
zq4.png [103.3 KB]
mp3.png [666.8 KB]
yarn4.png [70.9 KB]
image-大数据行业应用.png [526.8 KB]
image-bigdata01.png [546.4 KB]
zq9.png [260.6 KB]
yarn_architecture.gif [32.3 KB]
mp1.png [991.2 KB]
hadoop-hdfs1.png [29.3 KB]
mp6.png [916.5 KB]
mp5.png [863.2 KB]
zq13.png [148.3 KB]
mp4.png [461.0 KB]
image-hadoop1.png [433.1 KB]
zq6.png [8.5 KB]
image-mapreduce1.png [327.3 KB]
zq14.png [318.3 KB]
image-mapreduce.png [524.6 KB]
zq10.png [154.5 KB]
zq2.png [19.7 KB]
ha4.1.md [9.4 KB]
ha4.4.html [41.0 KB]
ha3.3.html [34.7 KB]
ha4.5.html [38.6 KB]
ha4.3.md [3.2 KB]
ha4.0.md [119.0 B]
ha3.0.html [30.7 KB]
ha3.0.md [99.0 B]
ha3.2.html [36.4 KB]
ha3.3.md [2.7 KB]
ha4.4.md [5.3 KB]
ha3.md [334.0 B]
ha3.4.html [37.3 KB]
ha4.1.html [50.6 KB]
ha3.html [30.5 KB]
ha4.5.md [3.5 KB]
ha3.5.html [47.4 KB]
ha3.1.md [3.6 KB]
ha3.5.md [7.9 KB]
ha3.1.html [37.5 KB]
ha4.3.html [35.9 KB]
ha4.0.html [29.2 KB]
ha4.2.html [36.7 KB]
ha4.2.md [3.3 KB]
ha3.2.md [3.2 KB]
ha3.4.md [3.3 KB]
📁 day08
📁 pics
kafka_6.png [60.6 KB]
kafka_16.png [51.2 KB]
1540349678122.png [37.2 KB]
kafka_10.png [238.6 KB]
kafka_15.png [56.2 KB]
spark2.PNG [12.0 KB]
kafka_7.png [393.8 KB]
1540350260244.png [223.5 KB]
s8.PNG [203.5 KB]
1540347375394.png [52.7 KB]
kafka_17.png [129.5 KB]
1540347389671.png [52.7 KB]
s6.PNG [102.5 KB]
kafka_13.png [222.3 KB]
s7.PNG [339.4 KB]
kafka_11.png [78.6 KB]
kafka_4.png [60.6 KB]
kafka_14.png [91.6 KB]
1540350201715.png [78.7 KB]
kafka_12.png [147.0 KB]
宽依赖和窄依赖.png [250.5 KB]
kafka_2.png [22.7 KB]
kafka_8.png [386.8 KB]
kafka_9.png [57.1 KB]
1540347254561.png [32.7 KB]
s5.PNG [143.6 KB]
1540350245310.png [223.5 KB]
kafka_3.png [83.6 KB]
1540347422756.png [102.2 KB]
s4.PNG [286.5 KB]
spark3.PNG [90.6 KB]
s2.PNG [16.6 KB]
s3.PNG [86.2 KB]
spark1.PNG [15.4 KB]
1540350674304.png [21.2 KB]
s1.PNG [19.0 KB]
1540349692086.png [47.4 KB]
kafka_5.png [253.0 KB]
📁 资料
access.log [2.9 MB]
user.txt [150.0 B]
ip.txt [13.7 MB]
20090121000132.394251.http.format [1.9 MB]
s1.3.md [655.0 B]
s.html [30.0 KB]
s1.2.html [33.0 KB]
s1.4.md [4.7 KB]
s1.5.html [36.7 KB]
s1.1.html [48.7 KB]
s1.2.md [1.4 KB]
s1.1.md [8.4 KB]
s1.3.html [30.5 KB]
s1.4.html [41.2 KB]
s1.6.md [4.8 KB]
s1.5.md [2.7 KB]
s1.6.html [42.1 KB]
s1.0.md [242.0 B]
s1.0.html [30.4 KB]
s.md [71.0 B]
📁 day07
📁 pics
k1.PNG [19.1 KB]
kafka_8.png [386.8 KB]
kafka_3.png [83.6 KB]
1540349678122.png [32.9 KB]
f2.png [114.3 KB]
k3.PNG [65.8 KB]
kafka_7.png [393.8 KB]
k4.PNG [18.2 KB]
1540350674304.png [21.2 KB]
kafka_13.png [222.3 KB]
1540350201715.png [78.7 KB]
kafka_4.png [60.6 KB]
kafka_15.png [56.2 KB]
1540347254561.png [32.7 KB]
k5.PNG [58.4 KB]
1540347375394.png [52.7 KB]
f3.png [36.9 KB]
kafka_16.png [51.2 KB]
1540347422756.png [102.2 KB]
宽依赖和窄依赖.png [250.5 KB]
kafka_2.png [22.7 KB]
f4.png [22.9 KB]
1540349692086.png [35.3 KB]
1540347389671.png [52.7 KB]
1540350260244.png [223.5 KB]
kafka_14.png [91.6 KB]
kafka_10.png [238.6 KB]
kafka_6.png [60.6 KB]
kafka_5.png [253.0 KB]
f1.png [447.0 KB]
kafka_12.png [147.0 KB]
k2.PNG [22.7 KB]
1540350245310.png [223.5 KB]
kafka_17.png [129.5 KB]
kafka_11.png [78.6 KB]
kafka_9.png [57.1 KB]
k1.2.md [4.8 KB]
f1.2.md [3.9 KB]
k1.5.html [36.7 KB]
f1.7.html [45.3 KB]
f1.6.html [39.1 KB]
k1.4.html [31.4 KB]
f1.0.md [382.0 B]
k1.0.md [454.0 B]
k1.3.html [37.0 KB]
k.md [160.0 B]
k1.5.md [3.1 KB]
f1.2.html [37.8 KB]
f1.3.html [29.7 KB]
f1.5.html [45.2 KB]
f1.1.md [2.5 KB]
k1.0.html [29.9 KB]
k1.1.html [35.8 KB]
k1.4.md [1.5 KB]
f1.5.md [10.0 KB]
f1.4.md [2.1 KB]
f1.3.md [301.0 B]
f1.1.html [35.3 KB]
k1.2.html [38.5 KB]
f1.6.md [6.7 KB]
k1.1.md [2.5 KB]
f1.4.html [32.7 KB]
f.md [300.0 B]
k1.3.md [3.5 KB]
f.html [30.6 KB]
f1.7.md [10.4 KB]
f1.0.html [31.5 KB]
📁 day10
📁 pics
ml24.png [27.8 KB]
env1.png [153.3 KB]
kafka_4.png [60.6 KB]
ml26.png [137.7 KB]
ss11.png [367.8 KB]
s7.PNG [339.4 KB]
ml25.png [21.3 KB]
ml35.png [11.8 KB]
1540347375394.png [52.7 KB]
kafka_11.png [78.6 KB]
ml29.png [94.9 KB]
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1540350201715.png [78.7 KB]
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kafka_15.png [56.2 KB]
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ss8.PNG [296.5 KB]
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ml11.png [174.8 KB]
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ss4.PNG [165.9 KB]
kafka_5.png [253.0 KB]
ss19.PNG [84.7 KB]
env3.PNG [20.6 KB]
ml08.png [233.1 KB]
ml10.png [215.3 KB]
kafka_12.png [147.0 KB]
kafka_13.png [222.3 KB]
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kafka_10.png [238.6 KB]
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ss1.png [328.2 KB]
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s12.PNG [305.8 KB]
ml14.png [98.7 KB]
s3.PNG [86.2 KB]
kafka_9.png [57.1 KB]
ml18.png [180.4 KB]
s14.PNG [128.0 KB]
宽依赖和窄依赖.png [250.5 KB]
ml32.png [16.7 KB]
1540350245310.png [223.5 KB]
s5.PNG [143.6 KB]
ml19.png [20.7 KB]
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kafka_6.png [60.6 KB]
ml02.png [119.5 KB]
ss15.png [157.0 KB]
1540347254561.png [32.7 KB]
ss3.PNG [376.6 KB]
ml37.png [45.5 KB]
kafka_8.png [386.8 KB]
s2.PNG [16.6 KB]
1540350674304.png [21.2 KB]
ss17.png [72.8 KB]
ss16.png [85.1 KB]
kafka_7.png [393.8 KB]
ml17.png [87.2 KB]
ss18.PNG [398.8 KB]
ml12.png [123.2 KB]
s11.PNG [232.2 KB]
ml20.png [40.7 KB]
ss13.png [166.8 KB]
env2.PNG [23.8 KB]
ss9.png [69.8 KB]
kafka_3.png [83.6 KB]
ss14.png [101.1 KB]
s10.PNG [79.2 KB]
s1.5.html [40.0 KB]
s1.0.md [339.0 B]
ml1.0.html [29.7 KB]
s1.1.md [2.9 KB]
s.md [115.0 B]
s1.4.md [9.0 KB]
s1.3.md [1.6 KB]
s1.2.html [30.9 KB]
s1.2.md [791.0 B]
s1.1.html [36.7 KB]
s.html [30.2 KB]
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s1.6.md [3.1 KB]
ml1.4.html [35.6 KB]
ml1.4.md [3.6 KB]
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ml1.3.html [39.7 KB]
ml1.1.html [40.6 KB]
ml1.2.md [8.6 KB]
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ml1.0.md [299.0 B]
s1.3.html [33.1 KB]
s1.0.html [31.4 KB]
ml1.3.md [5.0 KB]
ml1.2.html [45.4 KB]
s1.4 - 副本.md [7.8 KB]
s1.5.md [4.5 KB]
📁 day09
📁 pics
kafka_16.png [51.2 KB]
kafka_15.png [56.2 KB]
kafka_9.png [57.1 KB]
1540349692086.png [47.4 KB]
kafka_17.png [129.5 KB]
kafka_3.png [83.6 KB]
s13.PNG [297.4 KB]
kafka_8.png [386.8 KB]
kafka_10.png [238.6 KB]
s14.PNG [128.0 KB]
1540350245310.png [223.5 KB]
s1.PNG [19.0 KB]
kafka_11.png [78.6 KB]
1540350201715.png [78.7 KB]
s6.PNG [102.5 KB]
kafka_4.png [60.6 KB]
s12.PNG [305.8 KB]
s2.PNG [16.6 KB]
s9.PNG [292.5 KB]
s5.PNG [143.6 KB]
kafka_12.png [147.0 KB]
kafka_5.png [253.0 KB]
kafka_6.png [60.6 KB]
s10.PNG [79.2 KB]
kafka_14.png [91.6 KB]
s4.PNG [286.5 KB]
kafka_2.png [22.7 KB]
1540347254561.png [32.7 KB]
1540349678122(1).png [37.2 KB]
1540347422756.png [102.2 KB]
宽依赖和窄依赖.png [250.5 KB]
kafka_13.png [222.3 KB]
1540350674304.png [21.2 KB]
1540347375394.png [52.7 KB]
s11.PNG [232.2 KB]
s8.PNG [203.5 KB]
s3.PNG [86.2 KB]
kafka_7.png [393.8 KB]
1540347389671.png [52.7 KB]
1540350260244.png [223.5 KB]
s7.PNG [339.4 KB]
s1.1.html [35.2 KB]
s1.5.md [7.2 KB]
s1.1.md [2.4 KB]
s1.4.html [62.6 KB]
s1.2.md [7.8 KB]
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s.md [84.0 B]
s.html [29.9 KB]
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s1.3.md [6.5 KB]
s1.4.md [20.8 KB]
s1.0.md [186.0 B]
s1.2.html [47.9 KB]
s1.5.html [52.9 KB]
search_index.json [2.0 MB]
index.html [31.6 KB]
📁 day05
📁 img
📁 hdfs_read_write
k.jpg [53.1 KB]
i.jpg [157.6 KB]
h.jpg [156.2 KB]
e.jpg [156.9 KB]
b.jpg [138.3 KB]
d.jpg [137.8 KB]
c.jpg [135.7 KB]
a.jpg [135.6 KB]
g.jpg [155.1 KB]
j.jpg [156.4 KB]
image-MapReduce5.png [334.6 KB]
image-yarn2.png [652.6 KB]
image-大数据应用2.png [1.3 MB]
yarn_architecture.gif [32.3 KB]
mr_result.png [38.1 KB]
hadoop-生态.png [396.0 KB]
hadoop-hdfsarchitecture.png [39.6 KB]
yarn4.png [70.9 KB]
mp3.png [666.8 KB]
mp4.png [461.0 KB]
image-大数据行业应用.png [526.8 KB]
image-mapreduce1.png [327.3 KB]
hadoop-yarn3.png [96.4 KB]
image-大数据应用3.png [1008.5 KB]
image-mapreduce2.png [668.1 KB]
image-mapreduce.png [524.6 KB]
hdfs_arc.png [55.9 KB]
hadoop-yarn.jpg [34.5 KB]
mp5.png [863.2 KB]
mp1.png [991.2 KB]
image-yarn.png [656.7 KB]
image-MapReduce4.png [335.6 KB]
image-hadoop1.png [433.1 KB]
image-bigdata01.png [546.4 KB]
hadoop-hdfs1.png [29.3 KB]
mp6.png [916.5 KB]
image-mapreduce3.png [1.1 MB]
ha2.1.md [412.0 B]
ha1.2.md [1.3 KB]
ha2.7.md [268.0 B]
ha2.3.md [1.9 KB]
ha2.5.md [4.5 KB]
ha2.4.md [1.9 KB]
ha1.4.md [950.0 B]
ha2.2.md [522.0 B]
ha1.0.md [150.0 B]
ha.md [115.0 B]
ha2.6.md [2.1 KB]
ha2.0.md [212.0 B]
ha1.1.md [2.4 KB]
ha1.3.md [324.0 B]
ha1.5.md [256.0 B]
📁 day10
📁 pics
📁 a
s6.PNG [102.5 KB]
ss6.png [163.3 KB]
ml34.png [9.9 KB]
1540347375394.png [52.7 KB]
ss1.png [328.2 KB]
kafka_6.png [60.6 KB]
env5.png [178.3 KB]
宽依赖和窄依赖.png [250.5 KB]
ss10.png [52.1 KB]
ss8.PNG [296.5 KB]
ml27.png [10.5 KB]
env2.PNG [23.8 KB]
ml18.png [180.4 KB]
env1.png [153.3 KB]
ml29.png [94.9 KB]
kafka_15.png [56.2 KB]
ml33.png [27.4 KB]
kafka_9.png [57.1 KB]
kafka_16.png [51.2 KB]
kafka_13.png [222.3 KB]
ss11.png [367.8 KB]
ml26.png [137.7 KB]
kafka_2.png [22.7 KB]
ml08.png [233.1 KB]
ml01.png [66.3 KB]
ml03.png [97.6 KB]
ml21.png [65.4 KB]
ss18.PNG [398.8 KB]
s8.PNG [203.5 KB]
ml02.png [119.5 KB]
1540347254561.png [32.7 KB]
s1.PNG [19.0 KB]
1540350245310.png [223.5 KB]
kafka_14.png [91.6 KB]
s3.PNG [86.2 KB]
ml23.png [10.1 KB]
kafka_4.png [60.6 KB]
s13.PNG [297.4 KB]
ml14.png [98.7 KB]
ml07.png [74.2 KB]
ss13.png [166.8 KB]
ss3.PNG [376.6 KB]
ml10.png [215.3 KB]
kafka_5.png [253.0 KB]
s11.PNG [232.2 KB]
ml04.png [103.7 KB]
kafka_11.png [78.6 KB]
ss4.PNG [165.9 KB]
s12.PNG [305.8 KB]
ml35.png [11.8 KB]
ml11.png [174.8 KB]
s14.PNG [128.0 KB]
ss15.png [157.0 KB]
ml24.png [27.8 KB]
ss16.png [85.1 KB]
ss9.png [69.8 KB]
ml37.png [45.5 KB]
env4.png [191.5 KB]
ml15.png [172.6 KB]
1540349692086.png [47.4 KB]
ml17.png [87.2 KB]
kafka_17.png [129.5 KB]
ml36.png [187.9 KB]
ss12.png [98.3 KB]
1540350674304.png [21.2 KB]
1540350201715.png [78.7 KB]
ml19.png [20.7 KB]
kafka_8.png [386.8 KB]
1540349678122.png [37.2 KB]
ml22.png [23.7 KB]
kafka_12.png [147.0 KB]
s10.PNG [79.2 KB]
1540347389671.png [52.7 KB]
s5.PNG [143.6 KB]
ml31.png [95.6 KB]
ss19.PNG [84.7 KB]
s9.PNG [292.5 KB]
ml12.png [123.2 KB]
ss14.png [101.1 KB]
1540347422756.png [102.2 KB]
ml32.png [16.7 KB]
ss17.png [72.8 KB]
ml16.png [28.7 KB]
ml28.png [39.5 KB]
kafka_10.png [238.6 KB]
ml30.png [260.2 KB]
env3.PNG [20.6 KB]
ss7.png [87.9 KB]
ss5.PNG [43.9 KB]
ml05.png [83.5 KB]
ml13.png [25.2 KB]
1540350260244.png [223.5 KB]
s2.PNG [16.6 KB]
ml09.png [76.4 KB]
ss2.PNG [163.9 KB]
ml06.png [166.4 KB]
kafka_3.png [83.6 KB]
s7.PNG [339.4 KB]
ml25.png [21.3 KB]
s1.7.md [4.0 KB]
s1.6.md [3.1 KB]
s1.1.md [2.9 KB]
ml1.1.md [4.4 KB]
s1.4.md [9.0 KB]
s1.4 - 副本.md [7.8 KB]
s1.0.md [339.0 B]
ml1.3.md [5.0 KB]
ml1.0.md [299.0 B]
ml1.4.md [3.6 KB]
s1.3.md [1.6 KB]
s1.2.md [791.0 B]
ml1.2.md [8.6 KB]
s.md [115.0 B]
s1.5.md [4.5 KB]
SUMMARY.md [3.3 KB]
README.md [498.0 B]
📁 大数据框架压缩包
📁 类库
spark-streaming_2.11-2.3.0.jar [2.1 MB]
leiningen-2.8.1-standalone.jar [12.9 MB]
scala-library-2.11.8.jar [5.5 MB]
spark-streaming-kafka-0-8-assembly_2.11-2.1.1.jar [10.8 MB]
mysql-connector-java-5.1.47-bin.jar [983.9 KB]
commons-lang3-3.7.jar [487.9 KB]
mysql-connector-java-5.1.36.jar [949.2 KB]
commons-lang3-3.8.jar [490.1 KB]
java-json.jar [82.7 KB]
commons-lang3-3.8.1.jar [490.1 KB]
spark-streaming-kafka-0-8-assembly_2.11-2.3.0.jar [11.7 MB]
spark-streaming-flume-assembly_2.11-2.3.0.jar [2.3 MB]
Miniconda3-4.3.14-Linux-x86_64.sh [33.1 MB]
Python-2.7.14.tgz [16.4 MB]
kafka_2.11-1.1.0.tgz [54.3 MB]
讲义_20190616.zip [56.5 MB]
推荐系统资料-详细.zip [152.8 MB]
📁 视频
9，上午小结_.mp4 [60.0 MB]
4，mapreduce原理介绍_.mp4 [60.7 MB]
1，回顾_.mp4 [67.8 MB]
7，大数据与互联网产品结合_.mp4 [34.1 MB]
14，hive的安装部署_.mp4 [44.3 MB]
3，topN调试_.mp4 [21.1 MB]
12，Hive与传统数据库对比_.mp4 [14.9 MB]
16，内部表和外部表_.mp4 [24.4 MB]
2，topN实现_.mp4 [67.6 MB]
8，数据分析案例_.mp4 [30.6 MB]
17，分区表_.mp4 [44.5 MB]
10，什么是hive_.mp4 [14.4 MB]
6，hdfs的读写流程_.mp4 [79.8 MB]
13，hive的数据模型_.mp4 [27.8 MB]
15，hive的shell操作_.mp4 [28.5 MB]
18，动态分区_.mp4 [11.8 MB]
11，hive的架构_.mp4 [17.0 MB]
5，hadoop生态_.mp4 [26.0 MB]
思路.txt [2.4 KB]
📁 pdf
day05-hive.xmind [77.0 KB]
day03、day04-hadoop.xmind [140.8 KB]
day02-推荐系统算法.xmind [61.5 KB]
day01-推荐系统简介.xmind [87.3 KB]
📁 day06
📁 前天的spark-core资料
20090121000132.394251.http(1).format [1.9 MB]
access.log [2.9 MB]
ip.txt [13.7 MB]
📁 视频
4，spark介绍及其local模式启动_.mp4 [54.6 MB]
11，spark-core实现日志分析_.mp4 [116.6 MB]
5，RDD的两种常用操作_.mp4 [12.9 MB]
7，transformation算子-2_.mp4 [56.1 MB]
9，pycharm连接远程centos环境准备_.mp4 [13.0 MB]
4，RDD的概念和RDD的创建_.mp4 [113.7 MB]
6，tranformation算子-1_.mp4 [14.0 MB]
3，HBase的组件_.mp4 [139.9 MB]
8，action算子和两类算子的执行_.mp4 [16.7 MB]
2，HappyBase操作Hbase_.mp4 [73.6 MB]
10，spark实现wordcount_.mp4 [87.4 MB]
12，ip地址查询实现_.mp4 [148.0 MB]
1，回顾_.mp4 [49.7 MB]
📁 资料
HBase.xmind [140.8 KB]
Spark-core.xmind [111.9 KB]
SecureCRT keygen.zip [423.6 KB]
1.png [226.5 KB]
📁 _book
📁 day01_推荐系统介绍
📁 img
lambda1.png [136.6 KB]
usercf2.png [22.2 KB]
od2.png [4.0 KB]
firststart2.png [564.2 KB]
algorithm4.png [101.5 KB]
firststart.png [226.3 KB]
混合推荐方法.jpeg [142.4 KB]
lambda4.png [97.0 KB]
决策树.jpg [227.4 KB]
algorithm2.png [146.7 KB]
整体式-特征组合.jpeg [105.2 KB]
als1.png [183.0 KB]
similarity_calc1.png [21.5 KB]
recommend6.png [36.7 KB]
Rocchio-3.jpg [28.6 KB]
algorithm6.png [238.0 KB]
稠密评分数据集.png [17.9 KB]
cosine.png [48.2 KB]
itemcf1.png [103.4 KB]
similarity_calc9.png [56.7 KB]
基于用户的预测公式.jpg [18.6 KB]
recommend2.png [61.4 KB]
user-itemMatrix4.png [51.1 KB]
整体式混合方法.jpeg [103.6 KB]
隐因子模型介绍.jpg [158.2 KB]
RS基础技术架构.png [1.1 MB]
recommend4.png [103.7 KB]
Rocchio-1.jpg [18.5 KB]
algorithm5.png [187.2 KB]
jaccard.png [87.9 KB]
基于用户的协同过滤推荐.png [12.2 KB]
整体式-特征补充.jpeg [135.1 KB]
similarity_calc11.png [64.4 KB]
CF介绍.png [178.0 KB]
od.png [10.6 KB]
协同推荐评分数据集.jpg [65.8 KB]
knn1.png [63.8 KB]
user-itemMatrix2.png [86.2 KB]
lambda7.png [225.2 KB]
Pearson相关系数公式.jpg [29.0 KB]
recommend3.png [218.1 KB]
firststart1.png [537.2 KB]
整体式-特征混合.jpeg [105.2 KB]
knn2.png [56.7 KB]
user-itemMatrix3.png [37.9 KB]
lambda3.png [167.0 KB]
itemcf2.png [113.8 KB]
修正的余弦相似度公式.jpg [51.8 KB]
基于用户的协同过滤推荐1.png [91.2 KB]
基础CB推荐算法.jpg [18.2 KB]
基于物品的预测公式.jpg [22.5 KB]
recommend1.png [501.9 KB]
lambda5.png [58.1 KB]
RS基础业务架构.png [343.2 KB]
similarity_calc3.png [78.0 KB]
推荐流程.png [16.9 KB]
similarity_calc5.png [241.9 KB]
lambda6.png [85.4 KB]
algorithm7.png [308.0 KB]
稀疏评分数据集.png [18.0 KB]
similarity_calc2.png [255.8 KB]
usercf3.png [4.5 KB]
algorithm3.png [94.8 KB]
usercf1.png [71.8 KB]
基于物品的协同过滤推荐1.png [113.3 KB]
Rocchio-2.jpg [23.7 KB]
基于物品的协同过滤推荐.png [13.8 KB]
lambda2.png [199.9 KB]
user-itemMatrix.png [24.9 KB]
用户画像2.jpg [45.0 KB]
algorithm1.png [146.7 KB]
1545049355235.png [86.6 KB]
相似度计算示例.png [23.9 KB]
recommend7.jpeg [13.1 KB]
graph1.png [57.8 KB]
pearson.png [116.4 KB]
recommend5.png [250.6 KB]
07_ 推荐系统评估.html [35.6 KB]
01_推荐系统简介.html [35.7 KB]
02_推荐系统架构设计.md [2.1 KB]
04_案例--基于协同过滤的电影推荐.html [53.3 KB]
03_推荐算法.html [70.8 KB]
04_案例--基于协同过滤的电影推荐.md [11.0 KB]
02_推荐系统架构设计.html [33.4 KB]
01_推荐系统简介.md [3.1 KB]
06_算法实现：Item-Based CF 预测评分.md [6.9 KB]
07_ 推荐系统评估.md [3.0 KB]
03_推荐算法.md [16.4 KB]
08_ 推荐系统冷启动问题.html [33.0 KB]
05_算法实现：User-Based CF 预测评分.md [6.7 KB]
08_ 推荐系统冷启动问题.md [1.6 KB]
📁 Hive&HBase
📁 img
hbase8.png [4.5 KB]
hive.jpg [6.9 KB]
1542868458080.png [296.9 KB]
hbase13.png [61.5 KB]
hbase7.png [10.3 KB]
hbase10.png [261.4 KB]
hbase6_2.png [4.3 KB]
structure.jpg [102.0 KB]
1.png [119.1 KB]
hbase14.png [36.2 KB]
2017-12-27_173407.jpg [113.7 KB]
2.png [65.7 KB]
hbase12.png [170.8 KB]
table3.png [29.3 KB]
Consistency.png [5.7 KB]
table1.png [54.0 KB]
hbase6.png [13.1 KB]
2017-12-27_230420.jpg [67.8 KB]
2017-12-27_230552.jpg [44.8 KB]
3.png [71.0 KB]
spark-hadoop2.png [110.9 KB]
hbase13_2.png [13.1 KB]
hbase9.png [45.0 KB]
table2.png [76.7 KB]
2017-12-27_180515.jpg [35.2 KB]
hbase&hive.png [93.5 KB]
error.png [36.4 KB]
hbase5.png [72.1 KB]
hive.png [164.3 KB]
hive3.png [33.6 KB]
1542868466073.png [296.9 KB]
phoenix.png [106.3 KB]
2012121416.jpeg [52.9 KB]
sqoop.png [119.4 KB]
cap.jpg [8.8 KB]
1542868506661.png [299.8 KB]
hbase4.png [53.1 KB]
2017-12-27_231532.jpg [47.5 KB]
hbase11.png [172.1 KB]
2017-12-27_180706.jpg [102.0 KB]
hive2.jpg [144.8 KB]
2017-12-27_192757.jpg [27.7 KB]
2017-12-27_192040.jpg [32.1 KB]
hbase9_2.png [14.4 KB]
10_HBase组件.html [35.2 KB]
05_hbase简介与环境部署.md [3.2 KB]
01_hive介绍.html [42.1 KB]
02_hive的shell操作.md [6.1 KB]
SUMMARY.md [561.0 B]
06_hbase数据模型.md [2.6 KB]
03_Hive的函数和自定义函数.html [36.7 KB]
04_hive综合案例.html [51.8 KB]
06_hbase数据模型.html [35.0 KB]
05_hBase简介与环境部署.html [34.9 KB]
08_HappyBase操作HBase.md [6.7 KB]
07_hbase的安装与shell操作.html [52.3 KB]
10_HBase组件.md [3.0 KB]
03_hive的函数和自定义函数.md [4.0 KB]
09_HBase表设计.md [2.7 KB]
08_HappyBase操作HBase.html [43.9 KB]
04_hive综合案例.md [11.7 KB]
01_hive介绍.md [7.2 KB]
07_hbase的安装与shell操作.md [10.0 KB]
02_hive的shell操作.html [42.6 KB]
📁 day02_推荐算法
📁 img
稀疏评分数据集.png [18.0 KB]
recommend2.png [61.4 KB]
挖掘频繁项集.png [102.8 KB]
基于内容推荐1.png [158.7 KB]
偏置.png [361.4 KB]
recommend1.png [501.9 KB]
矩阵分解5.jpg [8.9 KB]
word2vec3.png [38.8 KB]
word2vec1.png [32.6 KB]
recommend3.png [218.1 KB]
LFM矩阵分解图解2.png [35.8 KB]
导数的四则运算.png [229.4 KB]
矩阵分解4.jpg [6.0 KB]
基于用户的协同过滤推荐1.png [91.2 KB]
word2vec2.png [34.4 KB]
fp-growth1.png [60.4 KB]
交叉验证过程.png [100.2 KB]
fp-growth2.png [13.4 KB]
基于物品的协同过滤推荐.png [13.8 KB]
关联规则数据示例.png [13.2 KB]
矩阵分解1.jpg [1.7 KB]
稠密评分数据集.png [17.9 KB]
基于用户的协同过滤推荐.png [12.2 KB]
apriori2.png [73.5 KB]
apriori1.png [151.8 KB]
基于物品的协同过滤推荐1.png [113.3 KB]
矩阵分解2.jpg [1.7 KB]
矩阵分解3.jpg [5.2 KB]
similarity_calc2.png [255.8 KB]
常见函数求导.png [229.6 KB]
推荐场景2-音乐.png [1.1 MB]
LFM矩阵分解图解.png [34.1 KB]
推荐场景1-电商.png [769.1 KB]
02_基于K最近邻的协同过滤推荐.md [1.3 KB]
03_基于回归模型的协同过滤推荐.html [90.3 KB]
06_BiasSVD算法实现.md [5.6 KB]
04_基于矩阵分解的协同过滤推荐.md [2.4 KB]
11_物品冷启动处理.md [9.6 KB]
08_物品画像.html [63.1 KB]
10_TOPN用户推荐.html [31.4 KB]
03_基于回归模型的协同过滤推荐.md [27.1 KB]
09_用户画像.html [37.2 KB]
01_基于模型的协同过滤推荐.md [586.0 B]
04_基于矩阵分解的协同过滤推荐.html [34.5 KB]
01_基于模型的协同过滤推荐.html [30.3 KB]
05_LFM算法实现.md [8.3 KB]
07_基于内容的推荐算法.html [35.0 KB]
05_LFM算法实现.html [46.7 KB]
06_BiasSVD算法实现.html [38.7 KB]
09_用户画像.md [3.2 KB]
07_基于内容的推荐算法.md [2.3 KB]
10_TOPN用户推荐.md [1.4 KB]
08_物品画像.md [13.2 KB]
📁 day06_Spark_sql&Spark_streaming
📁 pics
ss7.png [87.9 KB]
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kafka_10.png [238.6 KB]
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kafka_13.png [222.3 KB]
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ml01.png [66.3 KB]
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s3.PNG [86.2 KB]
s14.PNG [128.0 KB]
ml28.png [39.5 KB]
kafka_12.png [147.0 KB]
kafka_8.png [386.8 KB]
kafka_5.png [253.0 KB]
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kafka_11.png [78.6 KB]
s1.2.md [7.2 KB]
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s1.1.md [2.4 KB]
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ss1.3.html [41.8 KB]
📁 gitbook
📁 gitbook-plugin-sharing
buttons.js [2.8 KB]
📁 images
favicon.ico [4.2 KB]
apple-touch-icon-precomposed-152.png [4.7 KB]
📁 fonts
📁 fontawesome
fontawesome-webfont.eot [74.7 KB]
fontawesome-webfont.svg [382.4 KB]
fontawesome-webfont.woff2 [70.2 KB]
FontAwesome.otf [122.1 KB]
fontawesome-webfont.woff [88.3 KB]
fontawesome-webfont.ttf [149.2 KB]
📁 gitbook-plugin-mathjax
plugin.js [191.0 B]
📁 gitbook-plugin-lunr
lunr.min.js [14.7 KB]
search-lunr.js [1.6 KB]
📁 gitbook-plugin-splitter
splitter.css [503.0 B]
splitter.js [3.8 KB]
📁 gitbook-plugin-fontsettings
website.css [8.4 KB]
fontsettings.js [6.3 KB]
📁 gitbook-plugin-search
search.js [6.2 KB]
lunr.min.js [14.7 KB]
search.css [974.0 B]
search-engine.js [1.2 KB]
📁 gitbook-plugin-expandable-chapters-small
expandable-chapters-small.css [580.0 B]
expandable-chapters-small.js [2.0 KB]
📁 gitbook-plugin-highlight
website.css [30.7 KB]
ebook.css [2.8 KB]
style.css [51.5 KB]
gitbook.js [102.9 KB]
theme.js [110.6 KB]
📁 day07_推荐系统案例
📁 img
整体式混合方法.jpeg [103.6 KB]
user-itemMatrix2.png [86.2 KB]
similarity_calc6.png [56.5 KB]
itemcf1.png [103.4 KB]
CF介绍.png [178.0 KB]
similarity_calc14.png [24.5 KB]
RS基础业务架构.png [343.2 KB]
lambda5.png [58.1 KB]
algorithm6.png [238.0 KB]
similarity_calc13.png [55.6 KB]
Rocchio-3.jpg [28.6 KB]
1545049355235.png [86.6 KB]
lambda2.png [199.9 KB]
流水线式混合方法.jpeg [65.4 KB]
基础CB推荐算法.jpg [18.2 KB]
流水线式-级联式.jpeg [122.8 KB]
recommend2.png [61.4 KB]
Pearson相关系数公式.jpg [29.0 KB]
user-itemMatrix.png [24.9 KB]
相似度计算示例.png [23.9 KB]
itemcf2.png [113.8 KB]
usercf2.png [22.2 KB]
firststart1.png [537.2 KB]
userprofile1.jpeg [33.2 KB]
并行式-切换式.jpeg [153.7 KB]
recommend5.png [250.6 KB]
similarity_calc1.png [21.5 KB]
recommend4.png [103.7 KB]
并行式混合方法.jpeg [88.8 KB]
lambda4.png [97.0 KB]
firststart2.png [564.2 KB]
基于物品的预测公式.jpg [22.5 KB]
Rocchio-2.jpg [23.7 KB]
od2.png [4.0 KB]
lambda7.png [225.2 KB]
algorithm1(1).png [146.7 KB]
并行式-混杂式.jpeg [120.8 KB]
recommend1.png [501.9 KB]
整体式-特征补充.jpeg [135.1 KB]
整体式-特征混合.jpeg [105.2 KB]
graph1.png [57.8 KB]
用户画像2.jpg [45.0 KB]
recommend6.png [36.7 KB]
lambda3.png [167.0 KB]
usercf1.png [71.8 KB]
firststart.png [226.3 KB]
混合推荐方法.jpeg [142.4 KB]
决策树.jpg [227.4 KB]
流水线式-层叠式.jpeg [124.1 KB]
algorithm7.png [308.0 KB]
RS基础技术架构.png [1.1 MB]
并行式-加权式.jpeg [129.9 KB]
similarity_calc7.png [27.7 KB]
挖掘频繁项集.png [102.8 KB]
similarity_calc8.png [42.6 KB]
knn1.png [63.8 KB]
similarity_calc16.png [26.8 KB]
推荐流程.png [16.9 KB]
协同推荐评分数据集.jpg [65.8 KB]
similarity_calc5.png [241.9 KB]
similarity_calc9.png [56.7 KB]
od.png [10.6 KB]
隐因子模型介绍.jpg [158.2 KB]
lambda1.png [136.6 KB]
similarity_calc4.png [73.9 KB]
similarity_calc15.png [24.1 KB]
Rocchio-1.jpg [18.5 KB]
similarity_calc2.png [255.8 KB]
similarity_calc3.png [78.0 KB]
similarity_calc11.png [64.4 KB]
algorithm4.png [101.5 KB]
algorithm3.png [94.8 KB]
整体式-特征组合.jpeg [105.2 KB]
修正的余弦相似度公式.jpg [51.8 KB]
knn2.png [56.7 KB]
recommend7.jpeg [13.1 KB]
recommend3.png [218.1 KB]
user-itemMatrix3.png [37.9 KB]
algorithm2.png [146.7 KB]
similarity_calc12.png [104.2 KB]
基于用户的预测公式.jpg [18.6 KB]
als1.png [183.0 KB]
algorithm5.png [187.2 KB]
推荐知识库示例.jpeg [160.7 KB]
user-itemMatrix4.png [51.1 KB]
usercf3.png [4.5 KB]
lambda6.png [85.4 KB]
similarity_calc10.png [64.9 KB]
05_离线推荐处理.md [9.8 KB]
06_实时推荐.html [40.9 KB]
06_实时推荐.md [8.1 KB]
02_根据用户行为数据创建ALS模型并召回商品.md [23.0 KB]
02_根据用户行为数据创建ALS模型并召回商品.html [76.2 KB]
01_个性化电商广告推荐系统介绍.md [6.0 KB]
01_个性化电商广告推荐系统介绍.html [42.8 KB]
03_CTR预估数据准备.md [70.3 KB]
04_逻辑回归实现CTR预估.md [36.2 KB]
05_离线推荐处理.html [49.6 KB]
03_CTR预估数据准备.html [127.9 KB]
04_逻辑回归实现CTR预估.html [77.0 KB]
📁 day03_Hadoop
📁 img
📁 hdfs_read_write
e.jpg [156.9 KB]
b.jpg [138.3 KB]
c.jpg [135.7 KB]
i.jpg [157.6 KB]
g.jpg [155.1 KB]
h.jpg [156.2 KB]
j.jpg [156.4 KB]
k.jpg [53.1 KB]
a.jpg [181.6 KB]
d.jpg [137.8 KB]
cdh.png [49.0 KB]
hadoop-生态.png [396.0 KB]
hadoop-yarn3.png [96.4 KB]
bigdata_arcit.png [69.4 KB]
hadoop-hdfs1.png [29.3 KB]
hadoop-state1.png [115.4 KB]
hadoop-state.png [66.9 KB]
mp3.png [666.8 KB]
hdfs_arc.png [55.9 KB]
mp1.png [991.2 KB]
mp4.png [461.0 KB]
case4.png [16.2 KB]
hadoop-hdfsarchitecture1.jpg [94.0 KB]
image-大数据行业应用.png [526.8 KB]
case3.png [7.3 KB]
image-yarn.png [656.7 KB]
image-mapreduce2.png [668.1 KB]
mp6.png [916.5 KB]
image-MapReduce4.png [335.6 KB]
yarn_architecture.gif [32.3 KB]
image-mapreduce.png [524.6 KB]
yarn.jpg [321.0 KB]
hadoop-state2.png [67.6 KB]
image-mapreduce1.png [327.3 KB]
image-hadoop1.png [433.1 KB]
image-mapreduce3.png [1.1 MB]
mr_result.png [38.1 KB]
image-yarn2.png [652.6 KB]
image-MapReduce5.png [334.6 KB]
mp5.png [863.2 KB]
yarn4.png [70.9 KB]
case1.png [8.3 KB]
image-大数据应用2.png [1.3 MB]
image-bigdata01.png [546.4 KB]
case2.png [9.5 KB]
hadoop-hdfsarchitecture.png [39.6 KB]
hadoop-yarn.jpg [34.5 KB]
image-大数据应用3.png [1008.5 KB]
ha1.1.md [3.1 KB]
ha2.4.md [872.0 B]
ha1.3.html [29.0 KB]
ha1.3.md [355.0 B]
ha3.0.md [215.0 B]
ha2.1.html [30.0 KB]
ha2.3.md [420.0 B]
ha3.1.md [3.5 KB]
ha3.3.html [36.0 KB]
ha1.1.html [35.3 KB]
ha4.3.html [41.0 KB]
ha4.1.md [1.2 KB]
ha3.1.html [35.9 KB]
ha2.3.html [29.2 KB]
ha2.2.html [33.7 KB]
ha2.0.md [195.0 B]
ha2.5.md [2.3 KB]
ha2.4.html [30.1 KB]
ha3.2.html [31.2 KB]
ha2.5.html [34.5 KB]
ha1.0.md [136.0 B]
ha2.2.md [2.9 KB]
ha2.1.md [1.2 KB]
ha1.2.html [32.0 KB]
ha4.2.html [35.5 KB]
ha4.0.md [133.0 B]
ha3.4.md [3.4 KB]
ha3.5.md [1.6 KB]
ha4.3.md [5.0 KB]
ha3.5.html [31.9 KB]
ha3.3.md [3.1 KB]
ha1.2.md [1.8 KB]
ha4.1.html [31.1 KB]
ha4.2.md [3.2 KB]
ha3.2.md [1.3 KB]
📁 day05_Spark_core
📁 img
s2.PNG [16.6 KB]
createrdd.png [117.4 KB]
pyspark.png [40.5 KB]
spark2.png [98.3 KB]
spark3.png [137.4 KB]
spark1.png [80.6 KB]
s5.PNG [143.6 KB]
s6.PNG [102.5 KB]
createrdd2.png [153.1 KB]
sparkui.png [62.3 KB]
rdd_map.png [12.5 KB]
spark_core_3.html [43.8 KB]
spark_core_2.md [4.4 KB]
spark_core_3.md [6.2 KB]
spark_core_1.html [34.3 KB]
spark_core_4.md [4.3 KB]
spark_core_6.md [2.9 KB]
spark_core_5.html [37.5 KB]
spark_core_2.html [36.8 KB]
spark_core_1.md [2.6 KB]
spark_core_4.html [37.2 KB]
spark_core_6.html [34.7 KB]
spark_core_5.md [3.7 KB]
search_index.json [3.5 MB]
index.html [33.9 KB]
📁 day11-day17
📁 _book
📁 day14_15
📁 img
1545630651922.png [88.0 KB]
chrome_start.png [3.7 KB]
word2vec3.png [38.8 KB]
recommend2.png [145.1 KB]
1545630559725.png [104.3 KB]
recommend1.png [321.1 KB]
word2vec2.png [34.4 KB]
word2vec1.png [32.6 KB]
chapter4.md [50.9 KB]
chapter7.html [72.2 KB]
chapter2.md [32.9 KB]
chapter10.html [45.3 KB]
chapter5.html [40.8 KB]
chapter5.md [9.3 KB]
chapter1.md [1.9 KB]
chapter3.html [127.3 KB]
chapter3.md [63.9 KB]
chapter1.html [32.0 KB]
chapter6.md [13.1 KB]
chapter9.md [10.2 KB]
chapter8.html [60.5 KB]
chapter8.md [20.7 KB]
chapter6.html [51.3 KB]
chapter7.md [26.7 KB]
chapter9.html [52.1 KB]
chapter10.md [8.6 KB]
chapter2.html [74.3 KB]
chapter4.html [125.8 KB]
📁 gitbook
📁 gitbook-plugin-lunr
lunr.min.js [14.7 KB]
search-lunr.js [1.6 KB]
📁 images
favicon.ico [4.2 KB]
apple-touch-icon-precomposed-152.png [4.7 KB]
📁 gitbook-plugin-livereload
plugin.js [327.0 B]
📁 gitbook-plugin-sharing
buttons.js [2.8 KB]
📁 fonts
📁 fontawesome
fontawesome-webfont.eot [74.7 KB]
FontAwesome.otf [122.1 KB]
fontawesome-webfont.woff2 [70.2 KB]
fontawesome-webfont.ttf [149.2 KB]
fontawesome-webfont.woff [88.3 KB]
fontawesome-webfont.svg [382.4 KB]
📁 gitbook-plugin-highlight
website.css [30.7 KB]
ebook.css [2.8 KB]
📁 gitbook-plugin-search
search-engine.js [1.2 KB]
lunr.min.js [14.7 KB]
search.js [6.2 KB]
search.css [974.0 B]
📁 gitbook-plugin-fontsettings
fontsettings.js [6.3 KB]
website.css [8.4 KB]
style.css [51.5 KB]
theme.js [110.6 KB]
gitbook.js [102.9 KB]
📁 day16
📁 code
hbasemanager.py [1.1 KB]
happybase_demo.py [3.4 KB]
📁 img
hbase4.png [53.1 KB]
hbase13.png [61.5 KB]
2017-12-27_180706.jpg [102.0 KB]
hbase11.png [172.1 KB]
spark-hadoop2.png [110.9 KB]
2017-12-27_192757.jpg [27.7 KB]
2017-12-27_180515.jpg [35.2 KB]
cap.jpg [8.8 KB]
2.png [65.7 KB]
2017-12-27_192040.jpg [32.1 KB]
hbase6_2.png [4.3 KB]
1542868458080.png [296.9 KB]
2012121416.jpeg [52.9 KB]
hbase9.png [45.0 KB]
1.png [119.1 KB]
table1.png [54.0 KB]
hbase5.png [72.1 KB]
hbase9_2.png [14.4 KB]
hbase13_2.png [13.1 KB]
hbase8.png [4.5 KB]
structure.jpg [102.0 KB]
hbase&hive.png [93.5 KB]
2017-12-27_231532.jpg [47.5 KB]
table2.png [76.7 KB]
hbase14.png [36.2 KB]
hbase7.png [10.3 KB]
1542868506661.png [299.8 KB]
2017-12-27_173407.jpg [113.7 KB]
hbase12.png [170.8 KB]
2017-12-27_230420.jpg [67.8 KB]
phoenix.png [106.3 KB]
table3.png [29.3 KB]
hbase6.png [13.1 KB]
Consistency.png [5.7 KB]
3.png [71.0 KB]
2017-12-27_230552.jpg [44.8 KB]
1542868466073.png [296.9 KB]
hbase10.png [261.4 KB]
h4.md [6.7 KB]
h2.html [41.8 KB]
h8.md [1.4 KB]
h8.html [31.7 KB]
h4.html [40.5 KB]
h1.md [2.4 KB]
h2.md [6.9 KB]
h7.md [9.2 KB]
h3.md [3.0 KB]
h3.html [32.6 KB]
h5.md [1.4 KB]
HBase.md [39.1 KB]
h7.html [46.9 KB]
h0.md
h1.html [32.0 KB]
h6.md [9.5 KB]
h6.html [47.2 KB]
h5.html [29.3 KB]
📁 day17
📁 img
dist2.png [79.3 KB]
zkshell1.png [56.5 KB]
dist9.png [4.5 KB]
dist10.png [7.1 KB]
sm03.png [124.4 KB]
dist1.png [141.7 KB]
dist11.png [5.7 KB]
dist12.png [5.7 KB]
streaming2.png [19.9 KB]
zk3.png [26.2 KB]
dist7.png [10.9 KB]
dist4.png [6.2 KB]
zk4.png [38.8 KB]
1.png [16.1 KB]
zk1.png [441.7 KB]
dist8.png [12.3 KB]
zk5.png [54.8 KB]
streaming1.png [50.8 KB]
dist5.png [5.3 KB]
dist3.png [13.5 KB]
zk2.png [34.3 KB]
sm02.png [127.4 KB]
dist6.png [8.1 KB]
07_Zookeeper选举模式和伪分布式集群搭建.html [29.8 KB]
03_Zookeeper基本数据模型.md [3.3 KB]
09_kazoo操作zookeeper.html [30.0 KB]
05_Zookeeper_ACL权限.md [7.3 KB]
04_Zookeeper命令行.md [9.2 KB]
02_Zookeeper安装.md [1.9 KB]
01_Zookeeper简介.md [6.0 KB]
08_Zookeeper应用举例.html [27.3 KB]
07_Zookeeper选举模式和伪分布式集群搭建.md [1.8 KB]
10_storm入门.md [5.1 KB]
01_Zookeeper简介.html [42.6 KB]
12_python操作storm.html [29.4 KB]
09_kazoo操作zookeeper.md [1.5 KB]
08_Zookeeper应用举例.md [416.0 B]
06_Zookeeper四字命令.html [31.1 KB]
10_storm入门.html [35.6 KB]
03_Zookeeper基本数据模型.html [30.7 KB]
05_Zookeeper_ACL权限.html [36.0 KB]
12_python操作storm.md [2.2 KB]
04_Zookeeper命令行.html [38.4 KB]
11_storm核心概念.html [30.2 KB]
11_storm核心概念.md [1.8 KB]
06_Zookeeper四字命令.md [4.2 KB]
02_Zookeeper安装.html [29.6 KB]
📁 day11_12
📁 img
similarity_calc1.png [21.5 KB]
firststart.png [226.3 KB]
knn2.png [56.7 KB]
并行式-混杂式.jpeg [120.8 KB]
基于用户的预测公式.jpg [18.6 KB]
RS基础技术架构.png [1.1 MB]
lambda2.png [199.9 KB]
1545049355235.png [86.6 KB]
决策树.jpg [227.4 KB]
基础CB推荐算法.jpg [18.2 KB]
lambda6.png [85.4 KB]
流水线式混合方法.jpeg [65.4 KB]
algorithm7.png [308.0 KB]
firststart1.png [537.2 KB]
Pearson相关系数公式.jpg [29.0 KB]
lambda3.png [167.0 KB]
usercf3.png [4.5 KB]
itemcf1.png [103.4 KB]
similarity_calc14.png [24.5 KB]
algorithm6.png [238.0 KB]
knn1.png [63.8 KB]
协同推荐评分数据集.jpg [65.8 KB]
并行式-加权式.jpeg [129.9 KB]
整体式-特征混合.jpeg [105.2 KB]
similarity_calc16.png [26.8 KB]
recommend5.png [250.6 KB]
挖掘频繁项集.png [102.8 KB]
firststart2.png [564.2 KB]
usercf1.png [71.8 KB]
recommend4.png [103.7 KB]
similarity_calc7.png [27.7 KB]
similarity_calc10.png [64.9 KB]
用户画像2.jpg [45.0 KB]
similarity_calc13.png [55.6 KB]
similarity_calc15.png [24.1 KB]
userprofile1.jpeg [33.2 KB]
流水线式-级联式.jpeg [122.8 KB]
相似度计算示例.png [23.9 KB]
user-itemMatrix.png [24.9 KB]
lambda4.png [97.0 KB]
lambda5.png [58.1 KB]
并行式-切换式.jpeg [153.7 KB]
similarity_calc9.png [56.7 KB]
并行式混合方法.jpeg [88.8 KB]
usercf2.png [22.2 KB]
整体式-特征组合.jpeg [105.2 KB]
algorithm5.png [187.2 KB]
Rocchio-1.jpg [18.5 KB]
CF介绍.png [178.0 KB]
基于物品的预测公式.jpg [22.5 KB]
similarity_calc2.png [255.8 KB]
similarity_calc5.png [241.9 KB]
recommend7.jpeg [13.1 KB]
RS基础业务架构.png [343.2 KB]
修正的余弦相似度公式.jpg [51.8 KB]
similarity_calc4.png [73.9 KB]
graph1.png [57.8 KB]
similarity_calc3.png [78.0 KB]
similarity_calc8.png [42.6 KB]
recommend3.png [218.1 KB]
推荐知识库示例.jpeg [160.7 KB]
隐因子模型介绍.jpg [158.2 KB]
Rocchio-2.jpg [23.7 KB]
similarity_calc6.png [56.5 KB]
algorithm1.png [146.7 KB]
recommend1.png [501.9 KB]
lambda1.png [136.6 KB]
混合推荐方法.jpeg [142.4 KB]
lambda7.png [225.2 KB]
整体式混合方法.jpeg [103.6 KB]
Rocchio-3.jpg [28.6 KB]
spark02.PNG [25.1 KB]
od.png [10.6 KB]
recommend2.png [61.4 KB]
od2.png [4.0 KB]
similarity_calc11.png [64.4 KB]
als1.png [183.0 KB]
similarity_calc12.png [104.2 KB]
流水线式-层叠式.jpeg [124.1 KB]
algorithm2.png [146.7 KB]
algorithm4.png [101.5 KB]
spark01.PNG [18.5 KB]
user-itemMatrix3.png [37.9 KB]
itemcf2.png [113.8 KB]
整体式-特征补充.jpeg [135.1 KB]
user-itemMatrix4.png [51.1 KB]
algorithm3.png [94.8 KB]
user-itemMatrix2.png [86.2 KB]
recommend6.png [36.7 KB]
推荐流程.png [16.9 KB]
08_CTR预估数据准备.html [129.2 KB]
03_推荐系统架构设计.html [30.4 KB]
05_ 推荐系统冷启动问题.md [1.5 KB]
09_逻辑回归实现CTR预估.md [66.9 KB]
09_逻辑回归实现CTR预估.html [125.2 KB]
07_根据用户行为数据创建ALS模型并召回商品.md [26.0 KB]
06_个性化电商广告推荐系统介绍.md [6.1 KB]
04_推荐算法.html [57.6 KB]
08_CTR预估数据准备.md [71.9 KB]
推荐算法.md [12.7 KB]
推荐系统.md [216.0 KB]
离线推荐处理.md [12.1 KB]
10_离线推荐处理.html [46.8 KB]
01_推荐系统简介.md [3.7 KB]
07_根据用户行为数据创建ALS模型并召回商品.html [78.2 KB]
01_推荐系统简介.html [36.4 KB]
11_实时推荐.md [11.7 KB]
11_实时推荐.html [44.1 KB]
02_ 推荐系统评估.html [33.2 KB]
02_ 推荐系统评估.md [3.2 KB]
03_推荐系统架构设计.md [2.0 KB]
05_ 推荐系统冷启动问题.html [29.8 KB]
10_离线推荐处理.md [9.6 KB]
06_个性化电商广告推荐系统介绍.html [40.5 KB]
04_推荐算法.md [12.9 KB]
📁 day13
📁 code
udf.sql [4.2 KB]
udf.py [168.0 B]
udaf.py [993.0 B]
udaf.sh [175.0 B]
📁 img
hive.png [164.3 KB]
hive.jpg [6.9 KB]
error.png [36.4 KB]
sqoop.png [119.4 KB]
hive2.jpg [144.8 KB]
hive3.png [33.6 KB]
mysql.PNG [34.6 KB]
hive5.md [2.9 KB]
hive3.html [29.8 KB]
hive8.md [3.4 KB]
hive6.html [34.5 KB]
hive1.md [4.4 KB]
hive2.md [3.2 KB]
hive5.html [33.0 KB]
hive7.html [47.2 KB]
hive3.md [1.9 KB]
hive7.md [10.2 KB]
hive4.html [29.7 KB]
hive4.md [1.7 KB]
hive1.html [35.8 KB]
hive6.md [4.1 KB]
hive2.html [31.0 KB]
hive8.html [34.3 KB]
index.html [28.0 KB]
search_index.json [4.0 MB]
📁 day16
📁 img
hbase7.png [10.3 KB]
hbase6_2.png [4.3 KB]
1542868506661.png [299.8 KB]
cap.jpg [8.8 KB]
2017-12-27_231532.jpg [47.5 KB]
2017-12-27_192757.jpg [27.7 KB]
1.png [119.1 KB]
2017-12-27_180515.jpg [35.2 KB]
hbase9_2.png [14.4 KB]
table3.png [29.3 KB]
2017-12-27_192040.jpg [32.1 KB]
hbase12.png [170.8 KB]
hbase4.png [53.1 KB]
phoenix.png [106.3 KB]
1542868466073.png [296.9 KB]
hbase6.png [13.1 KB]
structure.jpg [102.0 KB]
table2.png [76.7 KB]
hbase10.png [261.4 KB]
hbase13_2.png [13.1 KB]
3.png [71.0 KB]
hbase&hive.png [93.5 KB]
2.png [65.7 KB]
spark-hadoop2.png [110.9 KB]
2017-12-27_230420.jpg [67.8 KB]
1542868458080.png [296.9 KB]
hbase5.png [72.1 KB]
hbase11.png [172.1 KB]
hbase8.png [4.5 KB]
2017-12-27_180706.jpg [102.0 KB]
2017-12-27_173407.jpg [113.7 KB]
hbase14.png [36.2 KB]
2017-12-27_230552.jpg [44.8 KB]
Consistency.png [5.7 KB]
table1.png [54.0 KB]
hbase9.png [45.0 KB]
2012121416.jpeg [52.9 KB]
hbase13.png [61.5 KB]
📁 code
hbasemanager.py [1.1 KB]
happybase_demo.py [3.4 KB]
h3.md [3.0 KB]
h5.md [1.4 KB]
h6.md [9.5 KB]
h1.md [2.4 KB]
h8.md [1.4 KB]
h0.md
h2(1).md [6.9 KB]
h4.md [6.7 KB]
h7.md [9.2 KB]
HBase.md [39.1 KB]
📁 day14_15
📁 img
chrome_start.png [3.7 KB]
recommend1.png [321.1 KB]
word2vec1.png [32.6 KB]
recommend2.png [145.1 KB]
word2vec3.png [38.8 KB]
1545630651922.png [88.0 KB]
word2vec2.png [34.4 KB]
1545630559725(1).png [104.3 KB]
chapter7.md [26.7 KB]
chapter6.md [13.1 KB]
chapter3.md [63.9 KB]
chapter10.md [8.6 KB]
chapter8.md [20.7 KB]
chapter4.md [50.9 KB]
chapter2.md [32.9 KB]
chapter9.md [10.2 KB]
chapter5.md [9.3 KB]
chapter1.md [1.9 KB]
📁 day11_12
📁 img
similarity_calc8.png [42.6 KB]
决策树.jpg [227.4 KB]
similarity_calc16.png [26.8 KB]
algorithm5.png [187.2 KB]
推荐知识库示例.jpeg [160.7 KB]
整体式-特征混合.jpeg [105.2 KB]
algorithm2.png [146.7 KB]
Pearson相关系数公式.jpg [29.0 KB]
相似度计算示例.png [23.9 KB]
recommend4.png [103.7 KB]
整体式-特征组合.jpeg [105.2 KB]
lambda1.png [136.6 KB]
流水线式-级联式.jpeg [122.8 KB]
recommend1.png [501.9 KB]
similarity_calc14.png [24.5 KB]
RS基础技术架构.png [1.1 MB]
lambda5.png [58.1 KB]
firststart1.png [537.2 KB]
1545049355235.png [86.6 KB]
并行式混合方法.jpeg [88.8 KB]
knn2.png [56.7 KB]
lambda2.png [199.9 KB]
lambda4.png [97.0 KB]
整体式混合方法.jpeg [103.6 KB]
spark02.PNG [25.1 KB]
recommend7.jpeg [13.1 KB]
od2.png [4.0 KB]
流水线式-层叠式.jpeg [124.1 KB]
itemcf1.png [103.4 KB]
隐因子模型介绍.jpg [158.2 KB]
algorithm6.png [238.0 KB]
knn1.png [63.8 KB]
基于用户的预测公式.jpg [18.6 KB]
user-itemMatrix3.png [37.9 KB]
Rocchio-2.jpg [23.7 KB]
similarity_calc15.png [24.1 KB]
并行式-加权式.jpeg [129.9 KB]
od.png [10.6 KB]
用户画像2.jpg [45.0 KB]
user-itemMatrix4.png [51.1 KB]
user-itemMatrix2.png [86.2 KB]
基础CB推荐算法.jpg [18.2 KB]
lambda3.png [167.0 KB]
挖掘频繁项集.png [102.8 KB]
firststart2.png [564.2 KB]
recommend5.png [250.6 KB]
流水线式混合方法.jpeg [65.4 KB]
similarity_calc13.png [55.6 KB]
similarity_calc4.png [73.9 KB]
RS基础业务架构.png [343.2 KB]
CF介绍.png [178.0 KB]
协同推荐评分数据集.jpg [65.8 KB]
recommend3.png [218.1 KB]
algorithm1.png [146.7 KB]
并行式-混杂式.jpeg [120.8 KB]
混合推荐方法.jpeg [142.4 KB]
algorithm4.png [101.5 KB]
整体式-特征补充.jpeg [135.1 KB]
similarity_calc1.png [21.5 KB]
similarity_calc7.png [27.7 KB]
als1.png [183.0 KB]
similarity_calc11.png [64.4 KB]
修正的余弦相似度公式.jpg [51.8 KB]
推荐流程.png [16.9 KB]
基于物品的预测公式.jpg [22.5 KB]
similarity_calc5.png [241.9 KB]
similarity_calc9.png [56.7 KB]
lambda7.png [225.2 KB]
algorithm3.png [94.8 KB]
spark01.PNG [18.5 KB]
similarity_calc12.png [104.2 KB]
similarity_calc6.png [56.5 KB]
userprofile1.jpeg [33.2 KB]
algorithm7.png [308.0 KB]
user-itemMatrix.png [24.9 KB]
firststart.png [226.3 KB]
graph1.png [57.8 KB]
recommend2.png [61.4 KB]
usercf1.png [71.8 KB]
lambda6.png [85.4 KB]
similarity_calc2.png [255.8 KB]
itemcf2.png [113.8 KB]
Rocchio-1.jpg [18.5 KB]
并行式-切换式.jpeg [153.7 KB]
Rocchio-3.jpg [28.6 KB]
usercf2.png [22.2 KB]
recommend6.png [36.7 KB]
usercf3.png [4.5 KB]
similarity_calc3.png [78.0 KB]
similarity_calc10.png [64.9 KB]
01_推荐系统简介.md [3.7 KB]
推荐算法.md [12.7 KB]
03_推荐系统架构设计.md [2.0 KB]
06_个性化电商广告推荐系统介绍.md [6.1 KB]
离线推荐处理.md [12.1 KB]
07_根据用户行为数据创建ALS模型并召回商品.md [26.0 KB]
11_实时推荐.md [11.7 KB]
04_推荐算法.md [12.9 KB]
推荐系统.md [216.0 KB]
10_离线推荐处理.md [9.6 KB]
08_CTR预估数据准备.md [71.9 KB]
02_ 推荐系统评估.md [3.2 KB]
09_逻辑回归实现CTR预估.md [66.9 KB]
05_ 推荐系统冷启动问题.md [1.5 KB]
📁 day13
📁 code
udf.sql [4.2 KB]
udaf.py [993.0 B]
udf.py [168.0 B]
udaf.sh [175.0 B]
📁 img
hive.jpg [6.9 KB]
hive(1).png [164.3 KB]
hive2.jpg [144.8 KB]
error.png [36.4 KB]
hive3.png [33.6 KB]
mysql.PNG [34.6 KB]
sqoop.png [119.4 KB]
hive4.md [1.7 KB]
hive1.md [4.4 KB]
hive2.md [3.2 KB]
hive5.md [2.9 KB]
hive7.md [10.2 KB]
hive3.md [1.9 KB]
hive6.md [4.1 KB]
hive8.md [3.4 KB]
📁 day17
📁 img
zk2.png [34.3 KB]
sm03.png [124.4 KB]
dist3.png [13.5 KB]
streaming1.png [50.8 KB]
zk5.png [54.8 KB]
sm02.png [127.4 KB]
dist7.png [10.9 KB]
dist11.png [5.7 KB]
dist12.png [5.7 KB]
zk4.png [38.8 KB]
dist2.png [79.3 KB]
zkshell1.png [56.5 KB]
dist6.png [8.1 KB]
dist8.png [12.3 KB]
zk1.png [441.7 KB]
streaming2.png [19.9 KB]
dist9.png [4.5 KB]
dist4.png [6.2 KB]
1.png [16.1 KB]
dist1.png [141.7 KB]
dist5.png [5.3 KB]
dist10.png [7.1 KB]
zk3.png [26.2 KB]
03_Zookeeper基本数据模型.md [3.3 KB]
01_Zookeeper简介.md [6.0 KB]
04_Zookeeper命令行.md [9.2 KB]
06_Zookeeper四字命令.md [4.2 KB]
05_Zookeeper_ACL权限.md [7.3 KB]
12_python操作storm.md [2.2 KB]
02_Zookeeper安装.md [1.9 KB]
11_storm核心概念.md [1.8 KB]
10_storm入门.md [5.1 KB]
07_Zookeeper选举模式和伪分布式集群搭建.md [1.8 KB]
09_kazoo操作zookeeper.md [1.5 KB]
08_Zookeeper应用举例.md [416.0 B]
README.md [253.0 B]
SUMMARY.md [3.3 KB]
推荐系统课后作业.md [7.5 KB]
推荐系统资料备份.zip [76.5 MB]
📁 08_风控业务
12_特征衍生案例代码实现1_.mp4 [68.0 MB]
02_风控业务介绍_.mp4 [79.3 MB]
04_特征工程_特征选择_.mp4 [50.9 MB]
14_特征衍生总结_.mp4 [9.4 MB]
07_建模基本套路_.mp4 [57.4 MB]
15_移动应用大赛背景介绍_.mp4 [23.6 MB]
11_特征衍生案例_.mp4 [27.3 MB]
16_移动应用大赛_特征工程_.mp4 [102.8 MB]
08_建模基本套路总结_.mp4 [12.6 MB]
17_移动应用大赛_模型融合_.mp4 [86.9 MB]
03_反欺诈规则可能用到的数据_.mp4 [13.8 MB]
09_特征单调性和分布稳定性_.mp4 [47.7 MB]
05_特征工程_特征选择_RFE_.mp4 [28.5 MB]
06_特征工程_特征选择_embeded_.mp4 [18.3 MB]
10_特征单调性和分布稳定性总结_.mp4 [21.9 MB]
18_内容总结_.mp4 [53.6 MB]
13_特征衍生案例代码实现2_.mp4 [36.9 MB]
📁 07_电商数据
17_Pandas的API介绍3_.mp4 [67.1 MB]
05_用户流失分析代码实现和结果分析_.mp4 [68.3 MB]
06_分类问题使用场景总结_.mp4 [27.2 MB]
03_分类问题算法概述_.mp4 [41.6 MB]
12_异常点检测isolationforest代码实现_.mp4 [29.1 MB]
01_内容回顾_.mp4 [22.4 MB]
11_异常点检测isolationforest_.mp4 [69.1 MB]
14_非结构化数据的处理_.mp4 [62.6 MB]
16_Pandas的API介绍2_.mp4 [35.0 MB]
04_用户流失分析思路说明_.mp4 [32.0 MB]
08_关联规则基本概念_.mp4 [66.4 MB]
13_异常点检测isolationforest可视化_.mp4 [41.7 MB]
02_电商数据回归分析_.mp4 [30.1 MB]
07_优惠券使用预测_.mp4 [39.5 MB]
10_公式建模类算法总结_.mp4 [28.5 MB]
09_关联规则实现_.mp4 [19.5 MB]
15_Pandas的API介绍1_.mp4 [88.0 MB]
📁 03_excel计算
12_会员存量增量分析_.mp4 [51.2 MB]
15_线上线下会员增量对比_.mp4 [14.6 MB]
03_excel计算函数_.mp4 [30.8 MB]
08_Excel文本处理函数_.mp4 [12.9 MB]
23_复购率计算实现_.mp4 [45.0 MB]
18_门店会员明细表_.mp4 [30.0 MB]
02_excel基本功能介绍_.mp4 [37.6 MB]
10_常见图形_.mp4 [11.6 MB]
04_excel逻辑函数_.mp4 [16.1 MB]
16_地区店均会员分析_1_.mp4 [34.1 MB]
01_内容回顾_.mp4 [28.1 MB]
06_vlookup和hlookup函数_.mp4 [27.4 MB]
11_会员分析概述_.mp4 [18.7 MB]
19_地区会销比计算_.mp4 [94.5 MB]
13_会员等级分布_.mp4 [28.3 MB]
14_会员整体占比分析_.mp4 [12.4 MB]
22_复购率计算分析_.mp4 [21.0 MB]
24_内容回顾_.mp4 [35.1 MB]
20_连带率计算_.mp4 [26.9 MB]
05_match和index函数_.mp4 [13.6 MB]
21_连带率计算完成_.mp4 [47.2 MB]
07_indirect实现二级菜单_.mp4 [20.4 MB]
09_Excel数据透视表_.mp4 [30.7 MB]
17_地区店均会员分析_2_.mp4 [37.9 MB]
📁 02_数据分析思路
10_内容回顾_.mp4 [19.3 MB]
03_数据分析套路_漏斗分析_.mp4 [14.4 MB]
01_数据分析套路_对比分析多维度分析_.mp4 [44.3 MB]
04_数据分析套路_渠道分析_.mp4 [13.2 MB]
02_数据分析套路_多维度分析案例_.mp4 [20.9 MB]
09_中小公司数据分析工作介绍_.mp4 [11.1 MB]
08_数据分析套路_日常工作介绍2_.mp4 [43.9 MB]
05_数据分析套路_分布分析_.mp4 [8.0 MB]
06_数据分析套路_留存分析_.mp4 [7.4 MB]
07_数据分析套路_日常工作介绍_.mp4 [17.2 MB]
📁 人工智能
📁 机器学习07
📁 2_其它资料
📁 4_源代码
📁 .idea
📁 inspectionProfiles
profiles_settings.xml [228.0 B]
4_源代码.iml [459.0 B]
modules.xml [274.0 B]
workspace.xml [27.6 KB]
misc.xml [212.0 B]
📁 .ipynb_checkpoints
文件的读取和存储-checkpoint.ipynb [16.2 KB]
交叉表和透视表-checkpoint.ipynb [72.0 B]
案例：癌症分类预测-良／恶性乳腺癌肿瘤预测-checkpoint.ipynb [581.0 B]
hello_jupyter-checkpoint.ipynb [72.0 B]
显示温度变化状况-checkpoint.ipynb [72.0 B]
使用matplotlib绘制sigmoid激活函数的图形-checkpoint.ipynb [22.8 KB]
ndarray介绍-checkpoint.ipynb [72.0 B]
特征选择-checkpoint.ipynb [72.0 B]
案例：泰坦尼克号乘客生存预测-checkpoint.ipynb [72.0 B]
数据的合并-checkpoint.ipynb [72.0 B]
Pandas介绍-checkpoint.ipynb [72.0 B]
缺失值的处理-checkpoint.ipynb [72.0 B]
Untitled1-checkpoint.ipynb [72.0 B]
分组与聚合-checkpoint.ipynb [72.0 B]
ndarray的基本操作-checkpoint.ipynb [44.5 KB]
特征工程-特征提取-checkpoint.ipynb [1.6 KB]
案例-鸢尾花种类预测-checkpoint.ipynb [2.9 KB]
探究用户对物品类别的喜好细分降维-checkpoint.ipynb [72.0 B]
癌症分类预测-checkpoint.ipynb [72.0 B]
预测facebook签到位置-checkpoint.ipynb [581.0 B]
常见图形的绘制-checkpoint.ipynb [72.0 B]
泰坦尼克号乘客生存预测-checkpoint.ipynb [72.0 B]
ndarray运算-checkpoint.ipynb [17.5 KB]
基本数据操作-checkpoint.ipynb [142.2 KB]
聚类算法-checkpoint.ipynb [72.0 B]
K-means聚类-checkpoint.ipynb [171.4 KB]
特征提取-checkpoint.ipynb [72.0 B]
scikit-learn中数据集介绍-checkpoint.ipynb [581.0 B]
案例：探究用户对物品类别的喜好-checkpoint.ipynb [72.0 B]
折线图绘制与显示-checkpoint.ipynb [72.0 B]
数据离散化-checkpoint.ipynb [22.2 KB]
K-近邻算法API演示-checkpoint.ipynb [581.0 B]
tf-idf-checkpoint.ipynb [72.0 B]
📁 data
📁 instacart
._orders.csv [4.0 KB]
._aisles.csv [4.0 KB]
aisles.csv [2.5 KB]
products.csv [2.1 MB]
._order_products__prior.csv [4.0 KB]
order_products__prior.csv [550.8 MB]
orders.csv [103.9 MB]
._products.csv [4.0 KB]
📁 .ipynb_checkpoints
3.k-means案例-checkpoint.ipynb [72.0 B]
factor_returns.csv [309.0 KB]
._factor_returns.csv [4.0 KB]
泰坦尼克号乘客生存预测.ipynb [4.7 KB]
._tree.dot [4.0 KB]
使用matplotlib绘制sigmoid激活函数的图形.ipynb [22.8 KB]
特征提取.ipynb [6.2 KB]
癌症分类预测.ipynb [26.6 KB]
tree.dot [3.3 KB]
📁 1_教学资料
📁 PUBG(竞赛)
📁 PUBG_to_stu
📁 data
test_V2.csv [107.9 MB]
train_V2.csv [629.0 MB]
📁 .ipynb_checkpoints
Untitled-checkpoint(1).ipynb [72.0 B]
pubg.md [3.4 KB]
《绝地求生》玩家排名预测.docx [16.5 MB]
._pubg.md [4.0 KB]
._《绝地求生》玩家排名预测.docx [4.0 KB]
📁 pubg(竞赛)参考模型
📁 data
train_V2.csv [629.0 MB]
test_V2.csv [107.9 MB]
📁 img
._img1.png [4.0 KB]
img3.png [42.9 KB]
._img3.png [4.0 KB]
._img2.png [4.0 KB]
img2.png [721.1 KB]
img1.png [376.5 KB]
📁 .ipynb_checkpoints
PUBG-checkpoint.ipynb [332.4 KB]
._《绝地求生》玩家排名预测.docx [4.0 KB]
PUBG.ipynb [336.0 KB]
《绝地求生》玩家排名预测.docx [16.5 MB]
Snipaste_2019-06-09_10-05-52.png [409.8 KB]
Snipaste_2019-06-09_17-07-30.png [374.4 KB]
._机器学习算法.xmind [4.0 KB]
Snipaste_2019-06-09_11-01-19.png [447.3 KB]
Snipaste_2019-06-09_11-47-53.png [497.2 KB]
._Snipaste_2019-06-09_10-46-31.png [4.0 KB]
._Snipaste_2019-06-09_17-07-30.png [4.0 KB]
._Snipaste_2019-06-09_10-10-43.png [4.0 KB]
._Snipaste_2019-06-09_10-05-52.png [4.0 KB]
Snipaste_2019-06-09_10-10-43.png [272.0 KB]
._Snipaste_2019-06-09_11-01-19.png [4.0 KB]
Snipaste_2019-06-09_10-46-31.png [788.2 KB]
Snipaste_2019-06-09_12-21-12.png [463.5 KB]
._Snipaste_2019-06-09_17-09-02.png [4.0 KB]
Snipaste_2019-06-09_15-19-59.png [415.0 KB]
._Snipaste_2019-06-09_11-09-27.png [4.0 KB]
._Snipaste_2019-06-09_15-39-18.png [4.0 KB]
._课后作业.md [4.0 KB]
._意见和建议.md [4.0 KB]
Snipaste_2019-06-09_15-39-18.png [479.2 KB]
Snipaste_2019-06-09_17-09-02.png [306.3 KB]
意见和建议.md [270.0 B]
._Snipaste_2019-06-09_11-47-53.png [4.0 KB]
._Snipaste_2019-06-09_17-05-03.png [4.0 KB]
._Snipaste_2019-06-09_12-21-12.png [4.0 KB]
Snipaste_2019-06-09_11-09-27.png [557.1 KB]
._Snipaste_2019-06-09_15-19-59.png [4.0 KB]
课后作业.md [67.0 B]
Snipaste_2019-06-09_17-05-03.png [370.2 KB]
机器学习算法.xmind [57.0 KB]
📁 3_视频
17.集成学习算法简介_.mp4 [9.5 MB]
20.今日总结_.mp4 [10.9 MB]
2.AUC指标的计算_.mp4 [7.7 MB]
12.文本特征提取_.mp4 [46.0 MB]
6.信息增益率_.mp4 [13.0 MB]
5.信息增益_.mp4 [31.1 MB]
13.泰坦尼克号乘客生存预测步骤分析_.mp4 [17.2 MB]
8.决策树构建的步骤_.mp4 [6.6 MB]
3.决策树算法简介_.mp4 [22.9 MB]
10.cart剪枝_.mp4 [14.7 MB]
19.随机森林_.mp4 [26.9 MB]
18.Bagging集成学习的原理_.mp4 [18.3 MB]
16.决策树的优缺点_.mp4 [3.4 MB]
14.泰坦尼克号乘客生存预测实现_.mp4 [23.6 MB]
1.昨日复习_.mp4 [37.3 MB]
7.基尼值和基尼指数_.mp4 [39.9 MB]
11.字典特征提取_.mp4 [18.5 MB]
9.常见决策树类型_.mp4 [8.1 MB]
4.熵的计算_.mp4 [20.8 MB]
15.决策树可视化_.mp4 [12.4 MB]
📁 机器学习01
📁 2_其它资料
📁 .ipynb_checkpoints
hello_jupyter-checkpoint.ipynb [606.0 B]
hello_world-checkpoint.ipynb [1.3 KB]
📁 4_源代码
📁 .ipynb_checkpoints
hello_jupyter-checkpoint.ipynb [1.1 KB]
绘图的基本步骤-checkpoint.ipynb [72.0 B]
hello_matplotlib-checkpoint.ipynb [72.0 B]
hello_jupyter.ipynb [1.6 KB]
📁 1_教学资料
📁 azure
📁 .ipynb_checkpoints
Untitled-checkpoint.ipynb [72.0 B]
._adult.data.csv [4.0 KB]
Azure机器学习模型搭建实验.doc [1.7 MB]
adult.data.csv [3.7 MB]
._Azure机器学习模型搭建实验.doc [4.0 KB]
._Snipaste_2019-05-31_12-15-49.png [4.0 KB]
Snipaste_2019-05-31_12-15-49.png [880.3 KB]
._课后作业.md [4.0 KB]
._Snipaste_2019-05-31_15-47-13.png [4.0 KB]
Snipaste_2019-05-31_11-57-05.png [1.0 MB]
._混淆矩阵.png [4.0 KB]
._Snipaste_2019-05-31_12-07-10.png [4.0 KB]
._Snipaste_2019-05-31_11-57-05.png [4.0 KB]
._Snipaste_2019-05-31_15-42-55.png [4.0 KB]
Snipaste_2019-05-31_15-47-13.png [582.4 KB]
Snipaste_2019-05-31_11-54-56.png [1.4 MB]
._Snipaste_2019-05-31_11-54-56.png [4.0 KB]
混淆矩阵.png [127.6 KB]
科学计算库.xmind [104.5 KB]
Snipaste_2019-05-31_15-42-55.png [671.3 KB]
._科学计算库.xmind [4.0 KB]
Snipaste_2019-05-31_12-07-10.png [458.9 KB]
课后作业.md [146.0 B]
📁 3_视频
12.半监督学习和强化学习_.mp4 [25.8 MB]
1.课程介绍_.mp4 [9.1 MB]
4.人工智能的主要分支_.mp4 [35.8 MB]
10.数据基本处理和特征工程_.mp4 [26.9 MB]
17.深度学习简介_.mp4 [21.2 MB]
15.拟合_.mp4 [13.9 MB]
5.人工智能的三要素_.mp4 [22.9 MB]
3.人工智能发展历程_.mp4 [22.1 MB]
2.人工智能概述_.mp4 [71.7 MB]
14.回归模型的评估_.mp4 [25.5 MB]
11.监督学习和无监督学习_.mp4 [17.1 MB]
18.Jupyter notebook的使用_.mp4 [39.7 MB]
6.什么是机器学习_.mp4 [10.5 MB]
8.机器学习工作流程_2_.mp4 [10.8 MB]
19.今日总结_.mp4 [13.5 MB]
13.分类模型的评估_.mp4 [26.1 MB]
7.机器学习工作流程_1_.mp4 [3.4 MB]
16.Azure机器学习模型搭建实验_.mp4 [39.5 MB]
9.机器学习的几个基本概念_.mp4 [31.3 MB]
📁 机器学习05
📁 3_视频
17.一个问题：机器学习算法是如何学习的_.mp4 [4.2 MB]
15.线性回归的应用_.mp4 [20.2 MB]
16.线性回归api初步使用_.mp4 [14.6 MB]
1.pandas案例_.mp4 [39.1 MB]
5.scikit-learn的数据集API介绍_.mp4 [21.8 MB]
12.预测facebook签到位置步骤分析_.mp4 [20.6 MB]
10.交叉验证和网格搜索_1_.mp4 [25.9 MB]
18.今日总结_.mp4 [16.2 MB]
8.去量纲化_.mp4 [39.6 MB]
9.鸢尾花种类预测步骤分析_.mp4 [8.4 MB]
11.交叉验证和网格搜索的使用_.mp4 [16.8 MB]
13.预测facebook签到位置案例实现_.mp4 [42.9 MB]
6.查看数据分布_.mp4 [17.5 MB]
14.线性回归的公式_.mp4 [15.4 MB]
11.KNN的优点和缺点_.mp4 [16.6 MB]
4.kd树查找最近点的方法_.mp4 [23.5 MB]
10.鸢尾花种类预测实现_.mp4 [16.1 MB]
7.数据集划分_.mp4 [10.9 MB]
2.昨日复习_.mp4 [18.6 MB]
3.kd树的构造方法_.mp4 [20.5 MB]
📁 1_教学资料
._Snipaste_2019-06-06_11-51-43.png [4.0 KB]
📁 2_其它资料
📁 4_源代码
📁 .ipynb_checkpoints
数据离散化-checkpoint.ipynb [22.2 KB]
facebook签到位置预测-checkpoint.ipynb [72.0 B]
分组与聚合-checkpoint.ipynb [72.0 B]
Pandas介绍-checkpoint.ipynb [72.0 B]
ndarray介绍-checkpoint.ipynb [72.0 B]
折线图绘制与显示-checkpoint.ipynb [72.0 B]
去量纲化-checkpoint.ipynb [72.0 B]
缺失值的处理-checkpoint.ipynb [72.0 B]
sklearn数据集的获取-checkpoint.ipynb [72.0 B]
线性回归api初步使用-checkpoint.ipynb [72.0 B]
获取数据集-checkpoint.ipynb [72.0 B]
Untitled2-checkpoint.ipynb [72.0 B]
数据基本处理-checkpoint.ipynb [72.0 B]
scikit-learn数据集API介绍-checkpoint.ipynb [3.4 KB]
Untitled4-checkpoint.ipynb [72.0 B]
hello_jupyter-checkpoint.ipynb [72.0 B]
Untitled-checkpoint.ipynb [3.4 KB]
K-近邻算法API演示-checkpoint.ipynb [581.0 B]
pandas案例-checkpoint.ipynb [72.0 B]
鸢尾花种类预测-checkpoint.ipynb [72.0 B]
Untitled1-checkpoint.ipynb [72.0 B]
波士顿房价预测-checkpoint.ipynb [72.0 B]
ndarray的基本操作-checkpoint.ipynb [44.5 KB]
scikit-learn中数据集介绍-checkpoint.ipynb [581.0 B]
查看数据分布与数据集划分-checkpoint.ipynb [72.0 B]
特征预处理-checkpoint.ipynb [72.0 B]
常见图形的绘制-checkpoint.ipynb [72.0 B]
文件的读取和存储-checkpoint.ipynb [16.2 KB]
交叉表和透视表-checkpoint.ipynb [72.0 B]
基本数据操作-checkpoint.ipynb [142.2 KB]
数据的合并-checkpoint.ipynb [72.0 B]
ndarray运算-checkpoint.ipynb [17.5 KB]
Untitled3-checkpoint.ipynb [72.0 B]
显示温度变化状况-checkpoint.ipynb [72.0 B]
案例-鸢尾花种类预测-checkpoint.ipynb [2.9 KB]
预测facebook签到位置-checkpoint.ipynb [72.0 B]
📁 data
📁 stock_data
📁 day
._day_ev1.h5 [4.0 KB]
._day_estpb_FY1.h5 [4.0 KB]
._day_employee.h5 [4.0 KB]
day_pre_close.h5 [41.8 MB]
day_open.h5 [40.9 MB]
._day_amt.h5 [4.0 KB]
day_close.h5 [41.6 MB]
._day_pre_close.h5 [4.0 KB]
._day_maxupordown.h5 [4.0 KB]
day_high.h5 [41.1 MB]
._day_ev2_to_ebitda.h5 [4.0 KB]
day_employee.h5 [2.0 MB]
._day_ev2.h5 [4.0 KB]
day_ev1.h5 [43.0 MB]
day_dividendyield2.h5 [40.9 MB]
._day_pb_lf.h5 [4.0 KB]
._day_open.h5 [4.0 KB]
day_eps_ttm.h5 [15.2 MB]
day_adjfactor.h5 [12.9 MB]
day_pb_lf.h5 [20.9 MB]
._day_adjfactor.h5 [4.0 KB]
._day_low.h5 [4.0 KB]
day_ev2_to_ebitda.h5 [43.6 MB]
._day_dividendyield2.h5 [4.0 KB]
._day_estpeg_FTM.h5 [4.0 KB]
day_low.h5 [40.9 MB]
._day_ev.h5 [4.0 KB]
._day_eps_ttm.h5 [4.0 KB]
day_estpb_FY1.h5 [40.9 MB]
._day_close.h5 [4.0 KB]
day_ev.h5 [41.4 MB]
day_maxupordown.h5 [1.2 MB]
day_estpeg_FTM.h5 [42.6 MB]
._day_high.h5 [4.0 KB]
day_ev2.h5 [43.0 MB]
day_amt.h5 [33.1 MB]
📁 list
._财务指标列表_financelist1.xlsx [4.0 KB]
📁 list
._stocklistA.h5 [4.0 KB]
📁 list
._财务指标列表_financelist2.xlsx [4.0 KB]
📁 list
._财务指标列表_financelist3.xlsx [4.0 KB]
📁 list
stocklistA.h5 [1.5 MB]
日线字段列表.xlsx [7.0 KB]
财务指标列表_financelist2.xlsx [13.4 KB]
财务指标列表_financelist3.xlsx [6.1 KB]
._日线字段列表.xlsx [4.0 KB]
财务指标列表_financelist1.xlsx [8.9 KB]
📁 finance
finance_ebitda_ttm.h5 [915.6 KB]
finance_ebit2_ttm.h5 [937.3 KB]
._finance_ebit.h5 [4.0 KB]
._finance_ebit_ttm2.h5 [4.0 KB]
finance_ebitda2_ttm.h5 [927.0 KB]
finance_ebit2.h5 [858.3 KB]
._finance_ebitdatointerestdebt.h5 [4.0 KB]
._finance_ebitda_ttm.h5 [4.0 KB]
._finance_ebitda.h5 [4.0 KB]
._finance_ebitdatosales.h5 [4.0 KB]
finance_ebit.h5 [924.6 KB]
finance_ebitdatointerest.h5 [492.9 KB]
finance_ebit_ttm2.h5 [933.7 KB]
._finance_ebitps.h5 [4.0 KB]
finance_ebitdatodebt.h5 [541.3 KB]
finance_ebitdaps.h5 [466.0 KB]
finance_ebitdatointerestdebt.h5 [551.5 KB]
._finance_ebit2_ttm.h5 [4.0 KB]
._finance_ebitda2_ttm.h5 [4.0 KB]
._finance_ebitdatointerest.h5 [4.0 KB]
finance_ebitps.h5 [941.9 KB]
._finance_ebit2.h5 [4.0 KB]
finance_ebitdatosales.h5 [542.2 KB]
._finance_ebitdatodebt.h5 [4.0 KB]
finance_ebitda.h5 [532.7 KB]
._finance_ebitdaps.h5 [4.0 KB]
📁 date
._transaction_date.csv [4.0 KB]
transaction_date.csv [77.4 KB]
📁 .ipynb_checkpoints
3.pandas高级数据处理-checkpoint.ipynb [72.0 B]
📁 FBlocation
._test.csv [4.0 KB]
train.csv [1.2 GB]
test.csv [261.2 MB]
._train.csv [4.0 KB]
stock_day.csv [67.6 KB]
._directory.csv [4.0 KB]
IMDB-Movie-Data.csv [302.5 KB]
._Sarcasm_Headlines_Dataset.json [4.0 KB]
dating.txt [25.5 KB]
._stock_day.csv [4.0 KB]
Sarcasm_Headlines_Dataset.json [5.4 MB]
directory.csv [3.9 MB]
._IMDB-Movie-Data.csv [4.0 KB]
._dating.txt [4.0 KB]
📁 .idea
📁 inspectionProfiles
profiles_settings.xml [228.0 B]
workspace.xml [27.6 KB]
modules.xml [274.0 B]
4_源代码.iml [459.0 B]
misc.xml [212.0 B]
查看数据分布与数据集划分.ipynb [54.5 KB]
去量纲化.ipynb [6.0 KB]
线性回归api初步使用.ipynb [2.3 KB]
鸢尾花种类预测.ipynb [7.8 KB]
sklearn数据集的获取.ipynb [1.6 KB]
pandas案例.ipynb [37.6 KB]
预测facebook签到位置.ipynb [9.4 KB]
📁 1_教学资料(1)
Snipaste_2019-06-06_10-52-01.png [601.8 KB]
机器学习算法.xmind [69.4 KB]
._机器学习算法.xmind [4.0 KB]
Snipaste_2019-06-06_11-51-43.png [487.2 KB]
._Snipaste_2019-06-06_17-11-28.png [4.0 KB]
Snipaste_2019-06-06_16-44-45.png [591.6 KB]
课后作业.md [125.0 B]
Snipaste_2019-06-06_12-05-51.png [339.4 KB]
._课后作业.md [4.0 KB]
Snipaste_2019-06-06_15-24-37.png [490.9 KB]
._Snipaste_2019-06-06_15-27-16.png [4.0 KB]
._Snipaste_2019-06-06_16-01-49.png [4.0 KB]
Snipaste_2019-06-06_15-20-10.png [499.9 KB]
Snipaste_2019-06-06_17-11-28.png [483.6 KB]
._Snipaste_2019-06-06_15-24-37.png [4.0 KB]
._Snipaste_2019-06-06_10-52-01.png [4.0 KB]
Snipaste_2019-06-06_15-27-16.png [509.4 KB]
._意见和建议.md [4.0 KB]
._Snipaste_2019-06-06_16-50-49.png [4.0 KB]
Snipaste_2019-06-06_16-50-49.png [516.6 KB]
._Snipaste_2019-06-06_17-21-44.png [4.0 KB]
Snipaste_2019-06-06_17-50-35.png [313.1 KB]
Snipaste_2019-06-06_17-21-44.png [380.5 KB]
意见和建议.md [113.0 B]
._Snipaste_2019-06-06_17-50-35.png [4.0 KB]
._Snipaste_2019-06-06_16-44-45.png [4.0 KB]
._Snipaste_2019-06-06_15-20-10.png [4.0 KB]
._Snipaste_2019-06-06_12-05-51.png [4.0 KB]
Snipaste_2019-06-06_16-01-49.png [957.8 KB]
📁 机器学习06
📁 2_其它资料
📁 3_视频
20.癌症分类预测实现_.mp4 [27.7 MB]
14.模型的保存和加载_.mp4 [11.3 MB]
11.正则化_.mp4 [20.4 MB]
15.逻辑回归简介_.mp4 [6.5 MB]
1.昨日复习_.mp4 [11.2 MB]
2.数学：求导_.mp4 [27.7 MB]
18.逻辑回归api介绍_.mp4 [4.5 MB]
9.波士顿房价预测_.mp4 [23.7 MB]
13.岭回归_.mp4 [9.9 MB]
8.波士顿房价预测步骤分析_.mp4 [11.4 MB]
3.机器学习算法是如何学习的_.mp4 [20.9 MB]
10.过拟合和欠拟合_.mp4 [17.4 MB]
5.线性回归的损失和优化_.mp4 [42.4 MB]
4.正规方程_.mp4 [35.5 MB]
22.ROC曲线的绘制_.mp4 [23.9 MB]
17.逻辑回归的损失以及优化_.mp4 [12.3 MB]
16.逻辑回归的原理_.mp4 [24.1 MB]
19.癌症分类预测步骤分析_.mp4 [7.7 MB]
6.梯度下降法_.mp4 [27.4 MB]
7.线性回归api再介绍_.mp4 [8.2 MB]
23.今日总结_.mp4 [12.5 MB]
21.分类评估方法_.mp4 [21.6 MB]
12.正则化线性模型_.mp4 [15.5 MB]
📁 4_源代码
📁 .idea
📁 inspectionProfiles
profiles_settings.xml [228.0 B]
modules.xml [274.0 B]
4_源代码(1).iml [459.0 B]
misc.xml [212.0 B]
workspace.xml [27.6 KB]
📁 data
📁 .ipynb_checkpoints
3.pandas高级数据处理-checkpoint.ipynb [72.0 B]
📁 FBlocation
train.csv [1.2 GB]
._test.csv [4.0 KB]
._train.csv [4.0 KB]
test.csv [261.2 MB]
📁 stock_data
📁 date
._transaction_date.csv [4.0 KB]
transaction_date.csv [77.4 KB]
📁 finance
._finance_ebitdatointerest.h5 [4.0 KB]
._finance_ebitdatointerestdebt.h5 [4.0 KB]
._finance_ebitda.h5 [4.0 KB]
._finance_ebitda_ttm.h5 [4.0 KB]
finance_ebit2.h5 [858.3 KB]
finance_ebitda_ttm.h5 [915.6 KB]
finance_ebitps.h5 [941.9 KB]
finance_ebitdatointerest.h5 [492.9 KB]
._finance_ebitps.h5 [4.0 KB]
finance_ebitda2_ttm.h5 [927.0 KB]
finance_ebitdaps.h5 [466.0 KB]
._finance_ebitdatosales.h5 [4.0 KB]
._finance_ebit2.h5 [4.0 KB]
finance_ebitdatodebt.h5 [541.3 KB]
finance_ebit_ttm2.h5 [933.7 KB]
finance_ebitda.h5 [532.7 KB]
finance_ebitdatointerestdebt.h5 [551.5 KB]
finance_ebit.h5 [924.6 KB]
finance_ebitdatosales.h5 [542.2 KB]
._finance_ebit.h5 [4.0 KB]
finance_ebit2_ttm.h5 [937.3 KB]
._finance_ebitdaps.h5 [4.0 KB]
._finance_ebit_ttm2.h5 [4.0 KB]
._finance_ebit2_ttm.h5 [4.0 KB]
._finance_ebitda2_ttm.h5 [4.0 KB]
._finance_ebitdatodebt.h5 [4.0 KB]
📁 day
day_ev1.h5 [43.0 MB]
day_low.h5 [40.9 MB]
day_pre_close.h5 [41.8 MB]
day_adjfactor.h5 [12.9 MB]
day_amt.h5 [33.1 MB]
day_high.h5 [41.1 MB]
._day_ev1.h5 [4.0 KB]
._day_close.h5 [4.0 KB]
._day_pb_lf.h5 [4.0 KB]
._day_estpeg_FTM.h5 [4.0 KB]
day_maxupordown.h5 [1.2 MB]
._day_dividendyield2.h5 [4.0 KB]
._day_low.h5 [4.0 KB]
day_estpeg_FTM.h5 [42.6 MB]
._day_ev2_to_ebitda.h5 [4.0 KB]
._day_amt.h5 [4.0 KB]
._day_high.h5 [4.0 KB]
._day_pre_close.h5 [4.0 KB]
day_dividendyield2.h5 [40.9 MB]
day_ev.h5 [41.4 MB]
._day_maxupordown.h5 [4.0 KB]
._day_employee.h5 [4.0 KB]
._day_open.h5 [4.0 KB]
day_pb_lf.h5 [20.9 MB]
day_close.h5 [41.6 MB]
._day_ev2.h5 [4.0 KB]
day_ev2.h5 [43.0 MB]
._day_eps_ttm.h5 [4.0 KB]
._day_estpb_FY1.h5 [4.0 KB]
day_ev2_to_ebitda.h5 [43.6 MB]
day_employee.h5 [2.0 MB]
day_estpb_FY1.h5 [40.9 MB]
day_eps_ttm.h5 [15.2 MB]
day_open.h5 [40.9 MB]
._day_adjfactor.h5 [4.0 KB]
._day_ev.h5 [4.0 KB]
📁 list
财务指标列表_financelist2.xlsx [13.4 KB]
._财务指标列表_financelist1.xlsx [4.0 KB]
财务指标列表_financelist3.xlsx [6.1 KB]
._stocklistA.h5 [4.0 KB]
._财务指标列表_financelist2.xlsx [4.0 KB]
._财务指标列表_financelist3.xlsx [4.0 KB]
日线字段列表.xlsx [7.0 KB]
财务指标列表_financelist1.xlsx [8.9 KB]
._日线字段列表.xlsx [4.0 KB]
stocklistA.h5 [1.5 MB]
directory.csv [3.9 MB]
._directory.csv [4.0 KB]
._dating.txt [4.0 KB]
._stock_day.csv [4.0 KB]
stock_day.csv [67.6 KB]
._Sarcasm_Headlines_Dataset.json [4.0 KB]
IMDB-Movie-Data.csv [302.5 KB]
Sarcasm_Headlines_Dataset.json [5.4 MB]
dating.txt [25.5 KB]
._IMDB-Movie-Data.csv [4.0 KB]
📁 .ipynb_checkpoints
K-近邻算法API演示-checkpoint.ipynb [581.0 B]
癌症分类预测-checkpoint.ipynb [72.0 B]
预测facebook签到位置-checkpoint.ipynb [72.0 B]
线性回归api初步使用-checkpoint.ipynb [72.0 B]
特征提取-checkpoint.ipynb [72.0 B]
基本数据操作-checkpoint.ipynb [142.2 KB]
波士顿房价预测-checkpoint.ipynb [72.0 B]
文件的读取和存储-checkpoint.ipynb [16.2 KB]
折线图绘制与显示-checkpoint.ipynb [72.0 B]
交叉表和透视表-checkpoint.ipynb [72.0 B]
肿瘤预测-checkpoint.ipynb [72.0 B]
分组与聚合-checkpoint.ipynb [72.0 B]
Pandas介绍-checkpoint.ipynb [72.0 B]
案例：癌症分类预测-良／恶性乳腺癌肿瘤预测-checkpoint.ipynb [581.0 B]
常见图形的绘制-checkpoint.ipynb [72.0 B]
数据的合并-checkpoint.ipynb [72.0 B]
Untitled1-checkpoint.ipynb [72.0 B]
文本特征提取-checkpoint.ipynb [72.0 B]
岭回归-checkpoint.ipynb [2.2 KB]
数据离散化-checkpoint.ipynb [22.2 KB]
ndarray介绍-checkpoint.ipynb [72.0 B]
scikit-learn中数据集介绍-checkpoint.ipynb [581.0 B]
hello_jupyter-checkpoint.ipynb [72.0 B]
特征工程：字典特征提取-checkpoint.ipynb [72.0 B]
ndarray运算-checkpoint.ipynb [17.5 KB]
显示温度变化状况-checkpoint.ipynb [72.0 B]
用pandas实现标准化-checkpoint.ipynb [72.0 B]
ndarray的基本操作-checkpoint.ipynb [44.5 KB]
缺失值的处理-checkpoint.ipynb [72.0 B]
案例-鸢尾花种类预测-checkpoint.ipynb [2.9 KB]
._Snipaste_2019-06-08_10-41-32.png [4.0 KB]
Snipaste_2019-06-08_15-43-42.png [354.1 KB]
Snipaste_2019-06-08_12-28-37.png [569.1 KB]
test.pkl [669.0 B]
Snipaste_2019-06-08_11-20-40.png [562.5 KB]
._Snipaste_2019-06-08_17-06-38.png [4.0 KB]
Snipaste_2019-06-08_17-23-31.png [409.2 KB]
Snipaste_2019-06-08_10-44-27.png [457.1 KB]
._Snipaste_2019-06-08_10-24-55.png [4.0 KB]
Snipaste_2019-06-08_09-51-25.png [479.7 KB]
._Snipaste_2019-06-08_11-20-40.png [4.0 KB]
波士顿房价预测.ipynb [6.9 KB]
Snipaste_2019-06-08_11-08-10.png [614.7 KB]
._Snipaste_2019-06-08_10-16-07.png [4.0 KB]
._Snipaste_2019-06-08_11-15-07.png [4.0 KB]
._Snipaste_2019-06-08_10-44-27.png [4.0 KB]
._Snipaste_2019-06-08_17-23-31.png [4.0 KB]
癌症分类预测.ipynb [4.1 KB]
._Snipaste_2019-06-08_12-28-37.png [4.0 KB]
._Snipaste_2019-06-08_11-08-10.png [4.0 KB]
Snipaste_2019-06-08_10-41-32.png [513.6 KB]
Snipaste_2019-06-08_10-16-07.png [538.2 KB]
._Snipaste_2019-06-08_15-43-42.png [4.0 KB]
Snipaste_2019-06-08_10-54-01.png [580.4 KB]
._Snipaste_2019-06-08_10-54-01.png [4.0 KB]
Snipaste_2019-06-08_17-06-38.png [403.5 KB]
._Snipaste_2019-06-08_09-51-25.png [4.0 KB]
._Snipaste_2019-06-08_16-10-17.png [4.0 KB]
Snipaste_2019-06-08_10-24-55.png [644.4 KB]
Snipaste_2019-06-08_16-10-17.png [494.1 KB]
用pandas实现标准化.ipynb [4.5 KB]
Snipaste_2019-06-08_11-15-07.png [581.1 KB]
📁 1_教学资料
人工神经元.png [62.4 KB]
._人工神经元.png [4.0 KB]
._激活函数.png [4.0 KB]
._机器学习算法.xmind [4.0 KB]
._课后作业.md [4.0 KB]
课后作业.md [67.0 B]
机器学习算法.xmind [56.5 KB]
激活函数.png [5.7 KB]
📁 机器学习03
📁 1_教学资料
._Snipaste_2019-06-03_11-00-16.png [4.0 KB]
._科学计算库.xmind [4.0 KB]
Snipaste_2019-06-03_16-36-38.png [400.4 KB]
._Snipaste_2019-06-03_16-36-38.png [4.0 KB]
Snipaste_2019-06-03_10-36-00.png [460.6 KB]
._Snipaste_2019-06-03_17-00-40.png [4.0 KB]
._课后作业.md [4.0 KB]
._意见和建议.md [4.0 KB]
课后作业.md [4.0 B]
Snipaste_2019-06-03_11-00-16.png [445.8 KB]
Snipaste_2019-06-03_17-00-40.png [342.3 KB]
意见和建议.md [167.0 B]
._Snipaste_2019-06-03_10-36-00.png [4.0 KB]
科学计算库.xmind [115.0 KB]
📁 3_视频
11.Multiindex和Series_.mp4 [18.8 MB]
8.Pandas介绍_2_.mp4 [17.8 MB]
19.文件读取和存储_.mp4 [52.3 MB]
6.数组与数组的运算_.mp4 [40.9 MB]
20.今日总结_.mp4 [19.2 MB]
5.矩阵乘法的性质_.mp4 [18.3 MB]
13.排序操作_.mp4 [12.6 MB]
3.统计运算_.mp4 [20.5 MB]
7.Pandas介绍_.mp4 [7.2 MB]
2.逻辑运算_.mp4 [29.7 MB]
16.累计统计函数_.mp4 [21.1 MB]
1.昨日复习_.mp4 [20.6 MB]
15.统计运算_.mp4 [17.4 MB]
9.【重点】 DataFrame介绍_1_.mp4 [18.9 MB]
12.索引操作和赋值操作_.mp4 [27.8 MB]
4.矩阵乘法_.mp4 [31.4 MB]
10.DataFrame的索引设置_.mp4 [17.6 MB]
18.Pandas画图_.mp4 [7.0 MB]
17.自定义运算_.mp4 [9.8 MB]
14.逻辑运算_.mp4 [30.2 MB]
📁 4_源代码
📁 .ipynb_checkpoints
文件的读取和存储-checkpoint.ipynb [16.2 KB]
hello_jupyter-checkpoint.ipynb [72.0 B]
统计运算-checkpoint.ipynb [72.0 B]
课后作业及反馈-checkpoint.ipynb [1.8 KB]
文件读取和存储-checkpoint.ipynb [72.0 B]
数组间运算-checkpoint.ipynb [72.0 B]
缺失值处理-checkpoint.ipynb [72.0 B]
Untitled-checkpoint.ipynb [72.0 B]
pandas 介绍-checkpoint.ipynb [72.0 B]
ndarray的基本操作-checkpoint.ipynb [44.5 KB]
数据的合并-checkpoint.ipynb [72.0 B]
显示温度变化状况-checkpoint.ipynb [72.0 B]
交叉表和透视表-checkpoint.ipynb [72.0 B]
缺失值的处理-checkpoint.ipynb [72.0 B]
常见图形的绘制-checkpoint.ipynb [72.0 B]
ndarray运算-checkpoint.ipynb [72.0 B]
分组与聚合-checkpoint.ipynb [72.0 B]
hello_pandas-checkpoint.ipynb [72.0 B]
pandas的基本操作-checkpoint.ipynb [72.0 B]
分组和聚合-checkpoint.ipynb [72.0 B]
数据合并-checkpoint.ipynb [72.0 B]
交叉表与透视表-checkpoint.ipynb [72.0 B]
折线图绘制与显示-checkpoint.ipynb [72.0 B]
高级处理-合并-checkpoint.ipynb [72.0 B]
高级处理-缺失值处理-checkpoint.ipynb [72.0 B]
ndarray介绍-checkpoint.ipynb [72.0 B]
基本数据操作-checkpoint.ipynb [72.0 B]
未命名-checkpoint.ipynb [72.0 B]
高级处理-数据离散化-checkpoint.ipynb [72.0 B]
数组的运算-checkpoint.ipynb [172.3 KB]
pandas的文件读取和存储-checkpoint.ipynb [72.0 B]
Pandas介绍-checkpoint.ipynb [72.0 B]
数据离散化-checkpoint.ipynb [69.6 KB]
📁 data
📁 .ipynb_checkpoints
3.pandas高级数据处理-checkpoint.ipynb [72.0 B]
📁 stock_data
📁 list
._财务指标列表_financelist3.xlsx [4.0 KB]
._stocklistA.h5 [4.0 KB]
._财务指标列表_financelist2.xlsx [4.0 KB]
._财务指标列表_financelist1.xlsx [4.0 KB]
._日线字段列表.xlsx [4.0 KB]
日线字段列表.xlsx [7.0 KB]
财务指标列表_financelist2.xlsx [13.4 KB]
stocklistA.h5 [1.5 MB]
财务指标列表_financelist1.xlsx [8.9 KB]
财务指标列表_financelist3.xlsx [6.1 KB]
📁 date
transaction_date.csv [77.4 KB]
._transaction_date.csv [4.0 KB]
📁 finance
._finance_ebitdatodebt.h5 [4.0 KB]
._finance_ebitda.h5 [4.0 KB]
finance_ebit.h5 [924.6 KB]
finance_ebitda_ttm.h5 [915.6 KB]
._finance_ebit2_ttm.h5 [4.0 KB]
finance_ebitdaps.h5 [466.0 KB]
finance_ebitps.h5 [941.9 KB]
finance_ebitda2_ttm.h5 [927.0 KB]
finance_ebit2.h5 [858.3 KB]
._finance_ebitda_ttm.h5 [4.0 KB]
finance_ebitda.h5 [532.7 KB]
finance_ebitdatosales.h5 [542.2 KB]
finance_ebit_ttm2.h5 [933.7 KB]
finance_ebitdatodebt.h5 [541.3 KB]
._finance_ebitdatointerest.h5 [4.0 KB]
finance_ebit2_ttm.h5 [937.3 KB]
._finance_ebitda2_ttm.h5 [4.0 KB]
._finance_ebit.h5 [4.0 KB]
._finance_ebitdaps.h5 [4.0 KB]
._finance_ebit_ttm2.h5 [4.0 KB]
finance_ebitdatointerest.h5 [492.9 KB]
._finance_ebitdatosales.h5 [4.0 KB]
._finance_ebit2.h5 [4.0 KB]
finance_ebitdatointerestdebt.h5 [551.5 KB]
._finance_ebitdatointerestdebt.h5 [4.0 KB]
._finance_ebitps.h5 [4.0 KB]
📁 day
._day_eps_ttm.h5 [4.0 KB]
._day_employee.h5 [4.0 KB]
._day_dividendyield2.h5 [4.0 KB]
day_low.h5 [40.9 MB]
day_pre_close.h5 [41.8 MB]
day_adjfactor.h5 [12.9 MB]
._day_ev2_to_ebitda.h5 [4.0 KB]
day_open.h5 [40.9 MB]
day_estpeg_FTM.h5 [42.6 MB]
._day_close.h5 [4.0 KB]
day_close.h5 [41.6 MB]
._day_pb_lf.h5 [4.0 KB]
day_high.h5 [41.1 MB]
._day_open.h5 [4.0 KB]
._day_adjfactor.h5 [4.0 KB]
day_maxupordown.h5 [1.2 MB]
._day_estpb_FY1.h5 [4.0 KB]
day_dividendyield2.h5 [40.9 MB]
day_amt.h5 [33.1 MB]
day_ev2.h5 [43.0 MB]
day_eps_ttm.h5 [15.2 MB]
day_employee.h5 [2.0 MB]
day_pb_lf.h5 [20.9 MB]
._day_high.h5 [4.0 KB]
day_estpb_FY1.h5 [40.9 MB]
._day_low.h5 [4.0 KB]
._day_estpeg_FTM.h5 [4.0 KB]
._day_amt.h5 [4.0 KB]
._day_maxupordown.h5 [4.0 KB]
day_ev1.h5 [43.0 MB]
._day_ev2.h5 [4.0 KB]
._day_ev.h5 [4.0 KB]
._day_ev1.h5 [4.0 KB]
day_ev.h5 [41.4 MB]
day_ev2_to_ebitda.h5 [43.6 MB]
._day_pre_close.h5 [4.0 KB]
IMDB-Movie-Data.csv [302.5 KB]
._directory.csv [4.0 KB]
directory.csv [3.9 MB]
stock_day.csv [67.6 KB]
Sarcasm_Headlines_Dataset.json [5.4 MB]
._IMDB-Movie-Data.csv [4.0 KB]
._Sarcasm_Headlines_Dataset.json [4.0 KB]
._stock_day.csv [4.0 KB]
pandas 介绍.ipynb [65.1 KB]
ndarray运算.ipynb [13.3 KB]
._test.csv [4.0 KB]
test_2.json [5.3 MB]
基本数据操作.ipynb [107.4 KB]
test.json [5.3 MB]
文件读取和存储.ipynb [4.2 KB]
test.csv [7.3 KB]
课后作业及反馈.ipynb [16.4 KB]
test.h5 [72.9 MB]
📁 2_其它资料
._周志华-机器学习_.pdf [4.0 KB]
周志华-机器学习_.pdf [85.7 MB]
📁 机器学习08
📁 3_视频
16.总复习_2_.mp4 [18.9 MB]
11.主成分分析PCA_.mp4 [15.0 MB]
2.boosting集成原理_.mp4 [31.1 MB]
9.算法优化_.mp4 [29.0 MB]
5.聚类算法简介_.mp4 [10.2 MB]
8.聚类的模型评估_.mp4 [35.6 MB]
14.今日总结_.mp4 [8.4 MB]
12.探究用户对物品类别的喜好_.mp4 [43.9 MB]
7.聚类算法实现流程（原理）_.mp4 [17.5 MB]
4.GBDT和XGBOOST_.mp4 [43.0 MB]
13.算法选择指导_.mp4 [8.8 MB]
3.bagging和boosting的区别_.mp4 [8.1 MB]
10.特征选择_.mp4 [51.9 MB]
6.聚类算法api初步使用_.mp4 [21.0 MB]
1.昨日复习_.mp4 [15.5 MB]
15.总复习_1_.mp4 [45.7 MB]
📁 4_源代码
📁 .idea
📁 inspectionProfiles
profiles_settings.xml [228.0 B]
misc.xml [212.0 B]
modules.xml [274.0 B]
4_源代码.iml [459.0 B]
workspace.xml [27.6 KB]
📁 .ipynb_checkpoints
案例：癌症分类预测-良／恶性乳腺癌肿瘤预测-checkpoint.ipynb [581.0 B]
Untitled1-checkpoint.ipynb [72.0 B]
探究用户对物品类别的喜好-checkpoint.ipynb [72.0 B]
数据的合并-checkpoint.ipynb [72.0 B]
常见图形的绘制-checkpoint.ipynb [72.0 B]
特征提取-checkpoint.ipynb [72.0 B]
分组与聚合-checkpoint.ipynb [72.0 B]
数据离散化-checkpoint.ipynb [22.2 KB]
案例：探究用户对物品类别的喜好-checkpoint.ipynb [72.0 B]
tf-idf-checkpoint.ipynb [72.0 B]
特征降维-checkpoint.ipynb [72.0 B]
文件的读取和存储-checkpoint.ipynb [16.2 KB]
案例：泰坦尼克号乘客生存预测-checkpoint.ipynb [72.0 B]
scikit-learn中数据集介绍-checkpoint.ipynb [581.0 B]
聚类算法-checkpoint.ipynb [72.0 B]
K-means聚类-checkpoint.ipynb [171.4 KB]
Pandas介绍-checkpoint.ipynb [72.0 B]
预测facebook签到位置-checkpoint.ipynb [581.0 B]
交叉表和透视表-checkpoint.ipynb [72.0 B]
hello_jupyter-checkpoint.ipynb [72.0 B]
显示温度变化状况-checkpoint.ipynb [72.0 B]
ndarray运算-checkpoint.ipynb [17.5 KB]
基本数据操作-checkpoint.ipynb [142.2 KB]
聚类算法api初步使用-checkpoint.ipynb [72.0 B]
折线图绘制与显示-checkpoint.ipynb [72.0 B]
案例-鸢尾花种类预测-checkpoint.ipynb [2.9 KB]
癌症分类预测-checkpoint.ipynb [72.0 B]
缺失值的处理-checkpoint.ipynb [72.0 B]
特征工程-特征提取-checkpoint.ipynb [1.6 KB]
ndarray介绍-checkpoint.ipynb [72.0 B]
K-近邻算法API演示-checkpoint.ipynb [581.0 B]
泰坦尼克号乘客生存预测-checkpoint.ipynb [72.0 B]
探究用户对物品类别的喜好细分降维-checkpoint.ipynb [72.0 B]
特征选择-checkpoint.ipynb [72.0 B]
ndarray的基本操作-checkpoint.ipynb [44.5 KB]
📁 data
📁 instacart
._aisles.csv [4.0 KB]
products.csv [2.1 MB]
order_products__prior.csv [550.8 MB]
orders.csv [103.9 MB]
._order_products__prior.csv [4.0 KB]
._orders.csv [4.0 KB]
._products.csv [4.0 KB]
aisles.csv [2.5 KB]
📁 .ipynb_checkpoints
3.k-means案例-checkpoint.ipynb [72.0 B]
._factor_returns.csv [4.0 KB]
factor_returns.csv [309.0 KB]
聚类算法api初步使用.ipynb [174.6 KB]
探究用户对物品类别的喜好.ipynb [9.1 KB]
特征降维.ipynb [4.5 KB]
📁 2_其它资料
📁 1_教学资料
Snipaste_2019-06-10_10-45-51.png [345.2 KB]
._Snipaste_2019-06-10_11-52-34.png [4.0 KB]
._Snipaste_2019-06-10_17-27-54.png [4.0 KB]
._Snipaste_2019-06-10_10-57-15.png [4.0 KB]
Snipaste_2019-06-10_10-12-29.png [615.1 KB]
._Snipaste_2019-06-10_12-03-25.png [4.0 KB]
._Snipaste_2019-06-10_16-36-27.png [4.0 KB]
._Snipaste_2019-06-10_09-48-41.png [4.0 KB]
机器学习算法.xmind [91.4 KB]
Snipaste_2019-06-10_09-48-41.png [382.8 KB]
._Snipaste_2019-06-10_17-22-37.png [4.0 KB]
Snipaste_2019-06-10_16-10-41.png [994.5 KB]
._Snipaste_2019-06-10_16-06-57.png [4.0 KB]
Snipaste_2019-06-10_09-41-36.png [164.4 KB]
._机器学习算法.xmind [4.0 KB]
Snipaste_2019-06-10_16-36-27.png [853.7 KB]
Snipaste_2019-06-10_16-50-19.png [427.2 KB]
Snipaste_2019-06-10_15-42-40.png [750.4 KB]
Snipaste_2019-06-10_17-22-37.png [858.5 KB]
意见和建议.md [228.0 B]
._Snipaste_2019-06-10_15-42-40.png [4.0 KB]
._Snipaste_2019-06-10_10-45-51.png [4.0 KB]
Snipaste_2019-06-10_11-52-34.png [385.9 KB]
Snipaste_2019-06-10_15-30-39.png [366.3 KB]
._Snipaste_2019-06-10_16-10-41.png [4.0 KB]
._Snipaste_2019-06-10_10-12-29.png [4.0 KB]
Snipaste_2019-06-10_10-57-15.png [498.5 KB]
._Snipaste_2019-06-10_09-41-36.png [4.0 KB]
Snipaste_2019-06-10_12-03-25.png [728.7 KB]
._Snipaste_2019-06-10_16-50-19.png [4.0 KB]
._意见和建议.md [4.0 KB]
Snipaste_2019-06-10_17-27-54.png [340.8 KB]
._Snipaste_2019-06-10_15-30-39.png [4.0 KB]
Snipaste_2019-06-10_10-06-15.png [460.4 KB]
._Snipaste_2019-06-10_10-06-15.png [4.0 KB]
._Snipaste_2019-06-10_10-50-11.png [4.0 KB]
Snipaste_2019-06-10_16-06-57.png [793.7 KB]
Snipaste_2019-06-10_10-50-11.png [523.5 KB]
📁 机器学习04
📁 2_其它资料
📁 4_源代码
📁 .ipynb_checkpoints
k近邻API演示-checkpoint.ipynb [72.0 B]
文件的读取和存储-checkpoint.ipynb [16.2 KB]
Pandas介绍-checkpoint.ipynb [72.0 B]
ndarray运算-checkpoint.ipynb [17.5 KB]
特征预处理-checkpoint.ipynb [72.0 B]
查看数据分布-checkpoint.ipynb [72.0 B]
鸢尾花种类预测-checkpoint.ipynb [72.0 B]
pandas数据高级处理-checkpoint.ipynb [72.0 B]
交叉表和透视表-checkpoint.ipynb [72.0 B]
常见图形的绘制-checkpoint.ipynb [72.0 B]
ndarray的基本操作-checkpoint.ipynb [44.5 KB]
hello_jupyter-checkpoint.ipynb [72.0 B]
案例-鸢尾花种类预测-checkpoint.ipynb [2.9 KB]
文件读取与存储-checkpoint.ipynb [72.0 B]
显示温度变化状况-checkpoint.ipynb [72.0 B]
数据集划分-checkpoint.ipynb [72.0 B]
ndarray介绍-checkpoint.ipynb [72.0 B]
k近邻算法api初步使用-checkpoint.ipynb [72.0 B]
K-近邻算法API演示-checkpoint.ipynb [581.0 B]
Pandas案例-checkpoint.ipynb [72.0 B]
scikit-learn中数据集介绍-checkpoint.ipynb [72.0 B]
数据的合并-checkpoint.ipynb [72.0 B]
数据离散化-checkpoint.ipynb [22.2 KB]
pandas高级数据处理-checkpoint.ipynb [72.0 B]
分组与聚合-checkpoint.ipynb [72.0 B]
基本数据操作-checkpoint.ipynb [142.2 KB]
scikit-learn数据集API介绍-checkpoint.ipynb [72.0 B]
折线图绘制与显示-checkpoint.ipynb [72.0 B]
Untitled-checkpoint.ipynb [72.0 B]
缺失值的处理-checkpoint.ipynb [72.0 B]
📁 data
📁 stock_data
📁 list
._日线字段列表.xlsx [4.0 KB]
._财务指标列表_financelist1.xlsx [4.0 KB]
._财务指标列表_financelist2.xlsx [4.0 KB]
stocklistA.h5 [1.5 MB]
财务指标列表_financelist1.xlsx [8.9 KB]
财务指标列表_financelist3.xlsx [6.1 KB]
财务指标列表_financelist2.xlsx [13.4 KB]
._stocklistA.h5 [4.0 KB]
._财务指标列表_financelist3.xlsx [4.0 KB]
日线字段列表.xlsx [7.0 KB]
📁 finance
finance_ebit2_ttm.h5 [937.3 KB]
finance_ebitda.h5 [532.7 KB]
._finance_ebitdatointerestdebt.h5 [4.0 KB]
finance_ebitdatointerest.h5 [492.9 KB]
finance_ebit2.h5 [858.3 KB]
finance_ebit_ttm2.h5 [933.7 KB]
._finance_ebitda.h5 [4.0 KB]
._finance_ebit2_ttm.h5 [4.0 KB]
._finance_ebit2.h5 [4.0 KB]
finance_ebitda2_ttm.h5 [927.0 KB]
finance_ebitdatointerestdebt.h5 [551.5 KB]
finance_ebitps.h5 [941.9 KB]
._finance_ebitda_ttm.h5 [4.0 KB]
._finance_ebitps.h5 [4.0 KB]
._finance_ebitdatodebt.h5 [4.0 KB]
._finance_ebitdatointerest.h5 [4.0 KB]
._finance_ebitdaps.h5 [4.0 KB]
finance_ebitda_ttm.h5 [915.6 KB]
finance_ebitdatodebt.h5 [541.3 KB]
finance_ebit.h5 [924.6 KB]
._finance_ebit_ttm2.h5 [4.0 KB]
finance_ebitdaps.h5 [466.0 KB]
._finance_ebitdatosales.h5 [4.0 KB]
._finance_ebitda2_ttm.h5 [4.0 KB]
._finance_ebit.h5 [4.0 KB]
finance_ebitdatosales.h5 [542.2 KB]
📁 date
._transaction_date.csv [4.0 KB]
transaction_date.csv [77.4 KB]
📁 day
day_adjfactor.h5 [12.9 MB]
day_maxupordown.h5 [1.2 MB]
._day_amt.h5 [4.0 KB]
._day_maxupordown.h5 [4.0 KB]
day_estpeg_FTM.h5 [42.6 MB]
._day_open.h5 [4.0 KB]
._day_pre_close.h5 [4.0 KB]
day_pre_close.h5 [41.8 MB]
._day_dividendyield2.h5 [4.0 KB]
._day_pb_lf.h5 [4.0 KB]
day_dividendyield2.h5 [40.9 MB]
._day_adjfactor.h5 [4.0 KB]
day_open.h5 [40.9 MB]
._day_estpb_FY1.h5 [4.0 KB]
._day_eps_ttm.h5 [4.0 KB]
day_amt.h5 [33.1 MB]
day_ev.h5 [41.4 MB]
._day_ev2_to_ebitda.h5 [4.0 KB]
._day_close.h5 [4.0 KB]
._day_low.h5 [4.0 KB]
._day_ev.h5 [4.0 KB]
._day_estpeg_FTM.h5 [4.0 KB]
day_pb_lf.h5 [20.9 MB]
day_estpb_FY1.h5 [40.9 MB]
day_high.h5 [41.1 MB]
day_low.h5 [40.9 MB]
day_close.h5 [41.6 MB]
._day_ev1.h5 [4.0 KB]
._day_high.h5 [4.0 KB]
day_eps_ttm.h5 [15.2 MB]
day_employee.h5 [2.0 MB]
day_ev1.h5 [43.0 MB]
._day_ev2.h5 [4.0 KB]
day_ev2.h5 [43.0 MB]
day_ev2_to_ebitda.h5 [43.6 MB]
._day_employee.h5 [4.0 KB]
📁 .ipynb_checkpoints
3.pandas高级数据处理-checkpoint.ipynb [72.0 B]
IMDB-Movie-Data.csv [302.5 KB]
Sarcasm_Headlines_Dataset.json [5.4 MB]
._Sarcasm_Headlines_Dataset.json [4.0 KB]
._IMDB-Movie-Data.csv [4.0 KB]
._dating.txt [4.0 KB]
dating.txt [25.5 KB]
._directory.csv [4.0 KB]
directory.csv [3.9 MB]
stock_day.csv [67.6 KB]
._stock_day.csv [4.0 KB]
pandas数据高级处理.ipynb [148.6 KB]
k近邻算法api初步使用.ipynb [2.3 KB]
📁 1_教学资料
Snipaste_2019-06-04_15-32-59.png [766.0 KB]
Snipaste_2019-06-04_16-32-32.png [404.2 KB]
Snipaste_2019-06-04_16-28-20.png [504.3 KB]
._Snipaste_2019-06-04_16-32-32.png [4.0 KB]
._Snipaste_2019-06-04_17-21-52.png [4.0 KB]
Snipaste_2019-06-04_16-50-11.png [700.2 KB]
._科学计算库.xmind [4.0 KB]
Snipaste_2019-06-04_16-47-40.png [589.1 KB]
._意见和建议.md [4.0 KB]
Snipaste_2019-06-04_12-26-05.png [535.9 KB]
._Snipaste_2019-06-04_16-28-20.png [4.0 KB]
科学计算库.xmind [94.4 KB]
._Snipaste_2019-06-04_11-03-01.png [4.0 KB]
._Snipaste_2019-06-04_16-47-40.png [4.0 KB]
._机器学习算法.xmind [4.0 KB]
._Snipaste_2019-06-04_12-26-05.png [4.0 KB]
Snipaste_2019-06-04_15-26-36.png [616.1 KB]
._Snipaste_2019-06-04_17-05-31.png [4.0 KB]
Snipaste_2019-06-04_11-56-17.png [410.4 KB]
Snipaste_2019-06-04_11-03-01.png [529.6 KB]
Snipaste_2019-06-04_17-05-31.png [775.8 KB]
._Snipaste_2019-06-04_15-26-36.png [4.0 KB]
._Snipaste_2019-06-04_11-56-17.png [4.0 KB]
._Snipaste_2019-06-04_15-32-59.png [4.0 KB]
Snipaste_2019-06-04_17-21-52.png [519.9 KB]
._Snipaste_2019-06-04_16-50-11.png [4.0 KB]
Snipaste_2019-06-04_10-04-34.png [406.1 KB]
._Snipaste_2019-06-04_17-16-28.png [4.0 KB]
._Snipaste_2019-06-04_11-44-42.png [4.0 KB]
._Snipaste_2019-06-04_10-04-34.png [4.0 KB]
意见和建议.md [178.0 B]
机器学习算法.xmind [84.7 KB]
Snipaste_2019-06-04_11-44-42.png [502.6 KB]
Snipaste_2019-06-04_11-59-57.png [401.6 KB]
Snipaste_2019-06-04_17-16-28.png [569.9 KB]
._Snipaste_2019-06-04_11-59-57.png [4.0 KB]
📁 3_视频
9.分组与聚合_2_.mp4 [21.4 MB]
10.KNN的原理及实现步骤_.mp4 [23.8 MB]
5.one_hot编码_.mp4 [19.6 MB]
1.昨日复习_.mp4 [21.3 MB]
13.距离的度量_2_.mp4 [25.0 MB]
15.kd树的原理_.mp4 [20.2 MB]
8.交叉表与透视表_.mp4 [43.2 MB]
6.数据合并_1_.mp4 [11.1 MB]
11.k近邻算法api初步使用_.mp4 [17.4 MB]
12.距离的度量_1_.mp4 [23.8 MB]
7.数据合并_2_.mp4 [31.5 MB]
9分组与聚合_1_.mp4 [6.9 MB]
4.数据离散化_.mp4 [26.7 MB]
14.K值的选择对模型的影响_.mp4 [15.7 MB]
2.缺失值处理_1_.mp4 [38.0 MB]
3.缺失值处理_2_.mp4 [12.3 MB]
16.今日总结_.mp4 [15.2 MB]
._Snipaste_2019-06-07_10-04-05.png [4.0 KB]
Snipaste_2019-06-07_12-08-39.png [488.0 KB]
Snipaste_2019-06-07_12-03-28.png [477.2 KB]
k近邻算法api初步使用.ipynb [2.0 KB]
._Snipaste_2019-06-07_11-15-06.png [4.0 KB]
Snipaste_2019-06-07_11-39-42.png [419.0 KB]
._Snipaste_2019-06-07_12-03-28.png [4.0 KB]
._Snipaste_2019-06-07_12-08-39.png [4.0 KB]
Snipaste_2019-06-07_12-14-46.png [520.1 KB]
._Snipaste_2019-06-07_11-39-42.png [4.0 KB]
._Snipaste_2019-06-07_11-53-22.png [4.0 KB]
Snipaste_2019-06-07_10-04-05.png [578.9 KB]
._Snipaste_2019-06-07_12-14-46.png [4.0 KB]
Snipaste_2019-06-07_11-53-22.png [534.5 KB]
Snipaste_2019-06-07_11-15-06.png [589.0 KB]
📁 机器学习02
📁 4_源代码
📁 .ipynb_checkpoints
基础绘图功能-checkpoint.ipynb [34.1 KB]
ndarray运算-checkpoint.ipynb [17.5 KB]
类型修改和去重-checkpoint.ipynb [72.0 B]
ndarray的计算-checkpoint.ipynb [72.0 B]
Numpy的基本操作-checkpoint.ipynb [581.0 B]
hello_numpy-checkpoint.ipynb [72.0 B]
常见图形绘制-checkpoint.ipynb [72.0 B]
折线图绘制与显示-checkpoint.ipynb [72.0 B]
hello_matplotlib-checkpoint.ipynb [72.0 B]
形状修改-checkpoint.ipynb [72.0 B]
基本操作-checkpoint.ipynb [72.0 B]
ndarray的索引和切片-checkpoint.ipynb [72.0 B]
ndarray和list效率对比-checkpoint.ipynb [72.0 B]
显示温度变化状况-checkpoint.ipynb [72.0 B]
逻辑运算-checkpoint.ipynb [72.0 B]
Untitled-checkpoint.ipynb [72.0 B]
ndarray的属性-checkpoint.ipynb [995.0 B]
ndarray的基本操作-checkpoint.ipynb [72.0 B]
ndarray的生成-checkpoint.ipynb [72.0 B]
Numpy-checkpoint.ipynb [581.0 B]
N维数组-ndarray-checkpoint.ipynb [72.0 B]
折线图(plot)与基础绘图功能-checkpoint.ipynb [72.0 B]
ndarray介绍-checkpoint.ipynb [72.0 B]
绘图基本操作（辅助显示层）-checkpoint.ipynb [72.0 B]
hello_jupyter-checkpoint.ipynb [72.0 B]
常见图形的绘制-checkpoint.ipynb [72.0 B]
test_1.png [1.2 KB]
test.png [28.3 KB]
._test.png [4.0 KB]
基础绘图功能.ipynb [229.1 KB]
hello_matplotlib.ipynb [44.8 KB]
N维数组-ndarray.ipynb [2.7 KB]
hello_numpy.ipynb [2.8 KB]
基本操作.ipynb [21.0 KB]
常见图形的绘制.ipynb [30.3 KB]
._test_1.png [4.0 KB]
📁 2_其它资料
意见和建议.md [345.0 B]
._意见和建议.md [4.0 KB]
📁 3_视频
18.正态分布数组生成_.mp4 [9.9 MB]
15.生成固定范围的数组_.mp4 [11.7 MB]
21.今日总结_.mp4 [14.0 MB]
6.同一坐标系绘制多根曲线_.mp4 [18.2 MB]
5.完善原始折线图_1_.mp4 [29.4 MB]
11.Numpy是什么_.mp4 [26.1 MB]
7.多个坐标系绘图_.mp4 [20.8 MB]
13.ndarray的属性_.mp4 [34.4 MB]
12.Numpy的优势_.mp4 [18.8 MB]
8.绘制函数图像_.mp4 [10.7 MB]
19.均匀分布和正态分布的直方图_.mp4 [10.2 MB]
4.保存图像_.mp4 [13.3 MB]
9.常见图形的意义_.mp4 [27.7 MB]
10.常见图形的绘制_.mp4 [15.2 MB]
1.昨日复习_.mp4 [6.5 MB]
17.正态分布_.mp4 [23.3 MB]
20.ndarray的基本操作_.mp4 [43.2 MB]
14.ndarray的生成_1_.mp4 [16.2 MB]
16.均匀分布数组生成_.mp4 [13.1 MB]
2.Matplotlib三层结构_.mp4 [20.8 MB]
3.画图的三个步骤_.mp4 [11.4 MB]
📁 1_教学资料
Snipaste_2019-06-01_16-34-04.png [549.3 KB]
Snipaste_2019-06-01_15-13-28.png [687.9 KB]
simhei.ttf [9.6 MB]
Snipaste_2019-06-01_15-21-32.png [324.2 KB]
._Snipaste_2019-06-01_16-42-14.png [4.0 KB]
Snipaste_2019-06-01_16-22-34.png [385.8 KB]
._simhei.ttf [4.0 KB]
._Snipaste_2019-06-01_15-21-32.png [4.0 KB]
._Snipaste_2019-06-01_16-34-04.png [4.0 KB]
科学计算库.xmind [100.4 KB]
._课后作业.md [4.0 KB]
._Snipaste_2019-06-01_16-22-34.png [4.0 KB]
课后作业.md [79.0 B]
._科学计算库.xmind [4.0 KB]
Snipaste_2019-06-01_11-58-07.png [336.8 KB]
Snipaste_2019-06-01_16-42-14.png [450.9 KB]
._Snipaste_2019-06-01_15-13-28.png [4.0 KB]
📁 1_教学资料
._Snipaste_2019-06-01_11-58-07.png [4.0 KB]
机器学习 (科学计算库).exe [112.3 MB]
机器学习 (算法篇).exe [87.1 MB]
📁 04_EXCEL-RFM
03_用户运营场景介绍_.mp4 [25.9 MB]
02_用户运营指标介绍_.mp4 [48.3 MB]
05_RFM的excel实现_.mp4 [29.7 MB]
07_RFM的Python实现思路分析_.mp4 [50.4 MB]
11_RFM结果解读_.mp4 [53.6 MB]
06_会员运营模型_.mp4 [44.9 MB]
09_RFM分群完成_.mp4 [32.9 MB]
04_用户运营相关模型_.mp4 [30.2 MB]
08_RFM的数据处理实现&RFM划分思路_.mp4 [83.2 MB]
12_RFM结果通过excel保存处理_.mp4 [16.3 MB]
10_RFM分布可视化_.mp4 [30.6 MB]
📁 11-爬虫部分
📁 10_爬虫项目之失信人被执行人名单
📁 04国家企业信用公告系统失信人信息爬取
15_国家企业信用公告系统爬虫_实现公告系统中间件_.mp4 [65.6 MB]
11_国家企业信用公告系统爬虫_确定请求_.mp4 [104.1 MB]
13_国家企业信用公告系统爬虫_生成爬虫与跳过原有的下载器中间件_.mp4 [28.8 MB]
14_国家企业信用公告系统爬虫_实现生成cookie的脚本_.mp4 [114.3 MB]
12_国家企业信用公告系统爬虫_解决传递cookie问题_.mp4 [196.3 MB]
16_国家企业信用公告系统爬虫_完善爬虫_.mp4 [131.2 MB]
📁 05总结
17_失信人名单爬虫项目总结_.pcwlenv [34.4 MB]
📁 02百度失信人信息爬取
05_百度失信人信息爬虫实现_.mp4 [92.2 MB]
06_保存失信人信息_.mp4 [116.5 MB]
04_百度失信人信息爬虫URL分析_.mp4 [66.3 MB]
07_下载器中间件_.mp4 [64.6 MB]
📁 03最高人民法院失信人信息爬取
09_最高人民法院失信人信息爬虫_.mp4 [71.7 MB]
10_最高人民法院失信人爬虫信息去重_.mp4 [46.3 MB]
08_最高人民法院失信人页面分析确定URL_.mp4 [70.7 MB]
📁 01需求与开发准备
01_需求_.mp4 [45.2 MB]
03_创建项目与定义数据模型_.mp4 [32.7 MB]
02_开发环境与技术选择_.mp4 [11.5 MB]
📁 04_爬虫请求管理
📁 03队列与Python
27.redis优先级队列测试与总结_.mp4 [62.3 MB]
20.redis共享资源竞争问题解决方案_.mp4 [155.5 MB]
29.请求管理代码实现分析_.mp4 [242.4 MB]
17.基于redis实现优先级队列的原理_.mp4 [203.4 MB]
23.redis分布式锁实现_.mp4 [134.3 MB]
24.redis分布式锁使用测试与bug调试_.mp4 [242.3 MB]
21.redis分布式锁实现原理_.mp4 [198.1 MB]
18.基于redis的优先级队列实现_.mp4 [321.7 MB]
13.python中临时队列介绍_.mp4 [159.0 MB]
30.请求管理模块使用测试_.mp4 [241.0 MB]
15.基于redis实现队列的原理_.mp4 [181.0 MB]
28.请求管理整体实现方案分析_.mp4 [173.0 MB]
25.redis分布式锁实现(补充)_.mp4 [176.3 MB]
19.redis共享资源竞争问题_.mp4 [171.5 MB]
26.解决redis优先级队列中的资源竞争问题_.mp4 [230.2 MB]
14.python中持久化队列介绍_.mp4 [114.9 MB]
22.redis分布式锁注意实现以及死锁_.mp4 [114.2 MB]
16.基于redis实现FIFO、LIFO队列_.mp4 [131.4 MB]
📁 04消息队列与Python
40.kafka的分区特征介绍_.mp4 [201.0 MB]
49.rabbitmq中的直连交换机_.mp4 [265.2 MB]
39.Docker中利用桥接网络模式启动kafka_.mp4 [113.3 MB]
47.rabbitmq中队列的特征_.mp4 [152.6 MB]
37.利用docker-compose启动kafka_.mp4 [190.1 MB]
38.confluent-kafka-python安装与使用_.mp4 [193.8 MB]
43.kafka中消费者数量与topic分区数之间的关系_.mp4 [125.1 MB]
50.rabbitmq中的主题交换机_.mp4 [89.0 MB]
32.消息队列介绍_.mp4 [78.0 MB]
35.kafka工作原理介绍(三)_.mp4 [96.1 MB]
51.rabbitmq中的扇形交换机_.mp4 [71.9 MB]
42.kafka的消费者组的特征_.mp4 [72.7 MB]
52.rabbitmq中的首部交换机_.mp4 [100.5 MB]
45.rabbitmq工作环境搭建介绍_.mp4 [157.1 MB]
44.rabbitmq工作原理介绍_.mp4 [216.7 MB]
41.向指定的分区生产和消费数据_.mp4 [229.6 MB]
48.rabbitmq中消费者的ack确认机制_.mp4 [196.5 MB]
33.kafka工作原理介绍(一)_.mp4 [51.3 MB]
36.kafka工作环境搭建介绍_.mp4 [122.5 MB]
34.kafka工作原理介绍(二)_.mp4 [53.2 MB]
53.消息队列与请求管理实现总结_.mp4 [104.2 MB]
📁 05断点续爬与增量抓取
54.利用请求管理实现断点续爬、增量抓取的思路分析_.mp4 [141.7 MB]
📁 02请求管理简介
11.请求缓冲与调度管理分析_.mp4 [64.6 MB]
6.请求去重代码初步实现_.mp4 [181.5 MB]
7.请求判断依据数据处理逻辑分析_.mp4 [290.5 MB]
10.请求去重模块测试(二)_.mp4 [189.3 MB]
12.请求调度原理分析_.mp4 [127.5 MB]
8.请求判断依据数据处理逻辑实现.mp4_.mp4 [308.4 MB]
5.请求去重的判断依据与实现逻辑_.mp4 [2.5 MB]
2.请求管理简介_.mp4 [53.1 MB]
9.请求去重模块测试(一)_.mp4 [136.2 MB]
4.去重方案代码调用_.mp4 [24.5 MB]
3.请求去重管理简介_.mp4 [57.4 MB]
📁 01课程介绍
1.爬虫中的请求管理课程概要_.mp4 [32.5 MB]
📁 06总结
55.总结_.mp4 [68.4 MB]
📁 01_Docker核心技术原理及其应用
📁 08Docker核心技术之仓库
5.向私有仓库下载镜像_.mp4 [16.5 MB]
1.Docker私有仓库了解_.mp4 [24.5 MB]
2.了解Docker私有仓库搭建_.mp4 [30.5 MB]
6.具备认证的私有仓库搭建_.mp4 [82.5 MB]
3.无认证的私有仓库搭建_.mp4 [124.6 MB]
8.Docker仓库阶段总结_.mp4 [4.5 MB]
4.向私有仓库上传镜像_.mp4 [74.8 MB]
7.使用具备认证功能的私有仓库_.mp4 [32.5 MB]
📁 10Docker核心技术之Docker-Compose
11.单机ELK部署之ELK介绍_.mp4 [93.9 MB]
14.单机ELK部署之启动elasticsearch_.mp4 [232.7 MB]
5.DockerQQComposeQQFile配置概览_.mp4 [148.5 MB]
20.多主机ELK部署之跨主机下的composeQQfile工作原理_.mp4 [70.9 MB]
26.多主机ELK部署之总结_.mp4 [114.5 MB]
23.多主机ELK部署之改写composeQQfile_.mp4 [82.5 MB]
25.多主机ELK部署之启动与调试bug（二）_.mp4 [157.5 MB]
9.部署小型web项目之docker-compose启动_.mp4 [124.1 MB]
27.DockerQQCompose阶段课程总结_.mp4 [3.4 MB]
2.DockerQQCompose工作原理介绍_.mp4 [59.4 MB]
18.单机ELK部署之总结_.mp4 [43.5 MB]
17.单机ELK部署之加入kibana实现完成部署（二）_.mp4 [65.2 MB]
12.单机ELK部署之composeQQfile撰写思路_.mp4 [66.5 MB]
1.DockerQQCompose课程介绍_.mp4 [42.5 MB]
10.部署小型wen项目之数据卷挂载_.mp4 [131.1 MB]
24.多主机ELK部署之启动与调试bug（一）_.mp4 [74.5 MB]
21.多主机ELK部署之步骤分析_.mp4 [12.2 MB]
15.单机ELK部署之加入Logstash_.mp4 [34.5 MB]
19.多主机ELK部署之swarm介绍_.mp4 [12.8 MB]
6.部署小型web项目之项目代码实现_.mp4 [39.2 MB]
4.了解DockerQQComposeQQFile_.mp4 [21.1 MB]
22.多主机ELK部署之composeQQfile中deploy参数概览_.mp4 [117.3 MB]
8.部署小型web项目之docker-compose文件撰写_.mp4 [41.2 MB]
7.部署小型web项目之Dockerfile实现_.mp4 [97.9 MB]
3.DockerQQCompose安装_.mp4 [73.9 MB]
16.单机ELK部署之加入kibana实现完成部署（一）_.mp4 [117.1 MB]
13.单机ELK部署之elasticsearch的composeQQfile撰写_.mp4 [125.0 MB]
📁 07Docker核心技术之数据卷
8.Docker数据卷管理之数据卷容器_.mp4 [23.8 MB]
9.Docker数据卷管理之volume方式数据卷的注意事项（一）_.mp4 [8.0 MB]
4.Docker数据卷管理之数据卷挂载方式介绍_.mp4 [35.3 MB]
2.Docker数据管理之数据卷简介（一）_.mp4 [26.3 MB]
12.Docker数据管理阶段总结_.mp4 [16.7 MB]
1.Docker数据管理之课程简介_.mp4 [7.8 MB]
6.Docker数据卷管理之volume方式挂载数据卷_.mp4 [97.5 MB]
5.Docker数据卷管理之bind方式挂载数据卷_.mp4 [12.0 MB]
3.Docker数据管理之数据卷简介（二）_.mp4 [33.9 MB]
7.Docker数据卷管理之tmpfs方式挂载数据卷_.mp4 [33.4 MB]
10.Docker数据卷管理之volume方式数据卷的注意事项（二）_.mp4 [26.0 MB]
11.Docker数据卷管理之volume方式数据卷的注意事项（三）_.mp4 [53.5 MB]
📁 06Docker核心技术之网络管理
14.Docker网络模式之Container网络模式原理_.mp4 [69.3 MB]
8.Docker网络管理之网络连接与断开_.mp4 [7.9 MB]
4.Docker网络管理之网络创建_.mp4 [131.8 MB]
10.Docker网络模式之bridge网络原理_.mp4 [123.0 MB]
2.了解Docker的网络管理_.mp4 [111.9 MB]
19.Docker网络模式之overlay网络的应用场景_.mp4 [77.2 MB]
20.Docker网络模式之macvlan网络模式原理_.mp4 [75.8 MB]
13.Docker网络模式之host网络模式原理_.mp4 [82.9 MB]
18.Docker网络模式之overlay网络模式实现原理_.mp4 [67.0 MB]
6.Docker网络管理之网络详细信息查看_.mp4 [5.4 MB]
11.Docker网络模式之定制bridge网络_.mp4 [80.1 MB]
1.Docker网络管理阶段课程简介_.mp4 [8.6 MB]
15.Docker网络模式之none网络介绍_.mp4 [3.8 MB]
16.Docker网络模式之overlay网络简介_.mp4 [46.7 MB]
21.Docker网络管理阶段总结_.mp4 [23.4 MB]
9.Docker网络模式之网络模式简介_.mp4 [6.8 MB]
5.Docker网络管理之网络删除_.mp4 [18.2 MB]
17.Docker网络模式之TCP、IP协议栈工作流程了解_.mp4 [34.9 MB]
7.Docker网络管理之网络使用_.mp4 [5.0 MB]
3.Docker网络管理之网络查看_.mp4 [36.3 MB]
12.Docker网络模式之bridge网络的端口映射_.mp4 [147.8 MB]
📁 05Docker核心技术之容器与镜像
2.Docker容器提交-docerkQQcommit_.mp4 [11.9 MB]
5.commit和import对比_.mp4 [96.8 MB]
6.联合文件系统与Docker镜像_.mp4 [134.3 MB]
3.Docker容器的导出-dockerQQexport_.mp4 [26.5 MB]
7.联合文件系统与容器_.mp4 [8.3 MB]
1.Docker容器与镜像的关系_.mp4 [17.8 MB]
4.Docker初始镜像构建-dockerQQimport_.mp4 [18.5 MB]
8.容器与镜像阶段总结_.mp4 [35.5 MB]
📁 03Docker核心技术之镜像
4.Docker镜像管理之镜像查看与下载（二）_.mp4 [17.4 MB]
11.Docker镜像管理之镜像历史信息查看_.mp4 [13.5 MB]
5.Docker镜像管理之镜像查看与下载（三）_.mp4 [22.6 MB]
9.Docker镜像管理之镜像重命名_.mp4 [6.3 MB]
6.Docker镜像管理之镜像删除_.mp4 [81.6 MB]
1.Docker镜像阶段课程介绍与镜像简介_.mp4 [8.5 MB]
7.Docker镜像管理之镜像保存与备份_.mp4 [5.9 MB]
2.镜像管理之镜像搜索以及镜像信息_.mp4 [27.5 MB]
12.Docker镜像阶段课程总结_.mp4 [2.9 MB]
3.Docker镜像管理之镜像查看与下载（一）_.mp4 [65.6 MB]
10.Docker镜像管理之镜像详细信息查看_.mp4 [19.5 MB]
8.Docker镜像管理之镜像还原导入_.mp4 [10.8 MB]
📁 04Docker核心技术之容器
5.了解虚拟机的生命周期_.mp4 [71.4 MB]
20.Docker容器运行时执行新命令QQdockerQQexec_.mp4 [67.4 MB]
6.了解容器的生命周期_.mp4 [57.8 MB]
7.Docker生命周期管理之容器创建dockerQQcreate（一）_.mp4 [107.6 MB]
17.Docker容器日志查看_.mp4 [66.1 MB]
8.Docker生命周期管理之容器创建dockerQQcreate（二）_.mp4 [61.4 MB]
22.Docker容器阶段课程总结_.mp4 [33.4 MB]
13.Docker生命周期管理之容器终止dockerQQkill_.mp4 [86.3 MB]
19.Docker容器连接QQdockerQQattach_.mp4 [77.0 MB]
15.Docker生命周期管理之容器重启dockerQQrestart_.mp4 [9.3 MB]
9.Docker生命周期管理之容器删除dockerQQrm_.mp4 [42.9 MB]
2.了解Docker容器_.mp4 [5.7 MB]
1.Docker容器阶段课程简介_.mp4 [12.9 MB]
21.attach和exec对比_.mp4 [40.7 MB]
10.Docker生命周期管理之容器启动dockerQQstart_.mp4 [140.2 MB]
14.Docker生命周期管理之容器暂停_.mp4 [27.8 MB]
3.容器与虚拟机对比（一）_.mp4 [55.3 MB]
16.Docker容器详细信息查看_.mp4 [39.9 MB]
11.Docker生命周期管理之容器创建并启动dockerQQrun_.mp4 [97.2 MB]
4.容器与虚拟机对比（二）_.mp4 [55.2 MB]
18.Docker容器重命名_.mp4 [17.3 MB]
12.Docker生命周期管理之容器关闭dockerQQstop_.mp4 [53.6 MB]
📁 02Docker版本与安装介绍
5.加速器配置方法_.mp4 [20.6 MB]
3.Ubuntu上安装Docker_.mp4 [12.6 MB]
6.Docker版本与安装阶段课程总结_.mp4 [37.1 MB]
4.Windows、MacOS安装Docker_.mp4 [3.6 MB]
2.CentOS上安装Docker_.mp4 [20.2 MB]
1.Docker安装与版本了解_.mp4 [5.6 MB]
📁 09Docker核心技术之Dockerfile
14.Dockerfile配置之ENV与ARG_.mp4 [60.3 MB]
4.利用Dockerfile构建镜像_.mp4 [159.7 MB]
16.Dockerfile配置之VOLUME_.mp4 [23.5 MB]
5.Dockerfile构建过程的特征_.mp4 [80.0 MB]
8.Dockerfile配置说明_.mp4 [41.6 MB]
13.Dockerfile配置之EXPOSE_.mp4 [35.6 MB]
9.Dockerfile配置之RUN_.mp4 [19.5 MB]
7.Dockerfile的命令与镜像层级的关系介绍_.mp4 [25.8 MB]
12.Dockerfile配置之LABEL与MAINTAINER_.mp4 [41.9 MB]
10.Dockerfile配置之shell格式命令与exec格式命令区别_.mp4 [56.1 MB]
6.Docekrfile构建的镜像的特征_.mp4 [184.6 MB]
11.Dockerfile配置之CMD与ENTRYPOINT_.mp4 [110.6 MB]
1.Dockerfile课程介绍_.mp4 [31.8 MB]
3.Dockerfile的撰写示范_.mp4 [8.4 MB]
15.Dockerfile配置之ADD与COPY_.mp4 [47.4 MB]
17.Dockerfile配置之USER和WORKDIR_.mp4 [22.4 MB]
18.Dockerfile配置之其他配置_.mp4 [50.2 MB]
2.了解Dockerfile_.mp4 [18.0 MB]
19.Dockerfile阶段总结_.mp4 [42.0 MB]
📁 01Docker概览
2.Docker概览阶段课程简介_.mp4 [8.1 MB]
6.Docker概览阶段课程总结_.mp4 [13.6 MB]
1.整体课程内容介绍_.mp4 [31.1 MB]
4.Docker整体结构了解_.mp4 [12.0 MB]
3.了解Docker_.mp4 [90.4 MB]
5.Docker底层技术了解_.mp4 [76.7 MB]
📁 06_爬虫异步任务设计
📁 03操作系统IO模型
5.异步IO_.mp4 [118.0 MB]
4.IO多路复用_.mp4 [130.4 MB]
6.同步IO和异步IO_.mp4 [85.2 MB]
3.非阻塞模式IO_.mp4 [77.2 MB]
1.IO操作本质_.mp4 [112.7 MB]
2.阻塞模式IO_.mp4 [89.5 MB]
📁 04IO设计模式
IO设计模式了解_.mp4 [213.0 MB]
📁 05Python爬虫与IO库
13.Gevent的协程池_.mp4 [102.4 MB]
9.Asyncio实现爬虫异步的方案_.mp4 [79.9 MB]
10.Greenlet与Yield对比_.mp4 [143.1 MB]
16.Twisted模块介绍_.mp4 [89.1 MB]
21.Twisted并发_.mp4 [47.0 MB]
3.Asyncio事件驱动代码练习_.mp4 [204.6 MB]
1.Python异步库使用介绍_.mp4 [51.7 MB]
6.Task的取消_.mp4 [57.3 MB]
2.Asyncio模块介绍_.mp4 [128.3 MB]
18.Twisted的Defered_.mp4 [37.4 MB]
24.Celery使用(一)_.mp4 [54.0 MB]
12.Gevent的猴子补丁_.mp4 [52.6 MB]
19.Agent模块发送请求_.mp4 [134.6 MB]
4.利用线程池执行Task_.mp4 [170.6 MB]
14.Tornado了解_.mp4 [53.5 MB]
17.Twisted的抽象层_.mp4 [87.2 MB]
7.EventLoop显示关闭_.mp4 [58.7 MB]
8.子线程中的EventLoop_.mp4 [139.6 MB]
23.Celery模块介绍_.mp4 [85.5 MB]
22.Twisted使用总结_.mp4 [73.9 MB]
5.协程的嵌套_.mp4 [163.8 MB]
20.Twisted获取响应数据_.mp4 [124.6 MB]
11.Gevent中的Greenlet_.mp4 [47.3 MB]
15.tornado的httpclient模块使用介绍_.mp4 [123.9 MB]
📁 06总结
总结_.mp4 [114.9 MB]
📁 01课程介绍
1.课程内容与环境介绍_.mp4 [38.3 MB]
📁 02进程、线程与协程
3.协程的实现方式_.mp4 [80.5 MB]
4.IO密集与计算密集_.mp4 [95.3 MB]
1.进程与线程简单对比_.mp4 [75.2 MB]
2.协程介绍_.mp4 [132.7 MB]
📁 09_ 反爬策略的应对机制
📁 03网站反爬策略应对
5.ADSL拨号代理实现原理_.mp4 [47.6 MB]
2.UA池的使用_.mp4 [24.7 MB]
3.代理池维护_.mp4 [97.4 MB]
4.代理IP的来源_.mp4 [146.8 MB]
1.应对反爬的基本思路_.mp4 [104.2 MB]
8.自动化解决验证码的方案_.mp4 [149.2 MB]
6.Cookie池使用_.mp4 [31.5 MB]
7.自动化构建加密参数的方案_.mp4 [112.3 MB]
📁 02网站反爬策略分析
2.网站如何识别爬虫.flv [184.1 MB]
1.网站为什么反爬_.mp4 [42.5 MB]
3.网站如何惩治爬虫_.mp4 [118.1 MB]
📁 04总结
1.课程总结_.mp4 [67.5 MB]
📁 01课程介绍
1.课程内容介绍_.mp4 [18.1 MB]
📁 05_爬虫数据处理
📁 01课程介绍
1.爬虫中的数据处理课程介绍_.mp4 [41.7 MB]
2.课程涉及系统环境介绍_.mp4 [64.3 MB]
📁 05总结
1.总结_.mp4 [81.5 MB]
📁 03爬虫数据存储
20.案例-mongoengine使用_.mp4 [71.5 MB]
10.案例-标签页抓取实现_.mp4 [77.0 MB]
16.案例-将数据存入json文件_.mp4 [38.4 MB]
15.案例-数据清洗_.mp4 [202.6 MB]
18.案例-sqlalchemy实现爬虫数据存储主逻辑_.mp4 [101.1 MB]
12.案例-列表页翻页实现_.mp4 [136.4 MB]
6.PyMySQL使用_.mp4 [215.2 MB]
2.文件存储_.mp4 [118.9 MB]
4.MySQL与PostgreSQL比较_.mp4 [193.3 MB]
8.PyMongo使用_.mp4 [114.0 MB]
5.MySQL与MongoDB比较_.mp4 [92.0 MB]
9.案例-需求分析介绍_.mp4 [105.2 MB]
11.案例-列表页抓取实现_.mp4 [59.1 MB]
3.数据库环境的搭建介绍_.mp4 [102.2 MB]
19.案例-django-orm的使用_.mp4 [181.1 MB]
14.案例-详情页抓取实现(二)_.mp4 [163.2 MB]
13.案例-详情页抓取实现(一)_.mp4 [183.3 MB]
7.psycopg2使用_.mp4 [112.3 MB]
1.爬虫数据存储介绍_.mp4 [40.0 MB]
17.案例-sqlalchemy建立模型类_.mp4 [210.6 MB]
📁 04爬虫数据清洗
1.爬虫数据清洗_.mp4 [100.0 MB]
📁 02爬虫数据解析与提取
11.正则表达式模块-re_.mp4 [168.3 MB]
2.爬虫数据解析与提取方案介绍_.mp4 [97.0 MB]
14.lxml模块使用介绍_.mp4 [193.4 MB]
9.正则表达式规则(六)_.mp4 [99.7 MB]
17.bs4使用介绍(二)_.mp4 [56.6 MB]
6.正则表达式规则(三)_.mp4 [126.9 MB]
15.css选择器规则与运用介绍_.mp4 [45.2 MB]
4.正则表达式规则(一)_.mp4 [301.8 MB]
10.正则表达式规则(七)_.mp4 [179.2 MB]
3.正则表达式规则与运用介绍_.mp4 [95.4 MB]
18.Pyquery使用介绍_.mp4 [75.1 MB]
24.pyexecjs模块使介绍_.mp4 [51.4 MB]
8.正则表达式规则(五)_.mp4 [135.5 MB]
5.正则表达式规则(二)_.mp4 [35.3 MB]
19.jsonpath规则与运用介绍_.mp4 [91.4 MB]
1.爬虫数据解析与提取介绍_.mp4 [213.6 MB]
21.解析规则小结_.mp4 [63.5 MB]
22.nodejs环境安装介绍_.mp4 [88.7 MB]
25.pyexecjs模块使用_.mp4 [144.0 MB]
23.js2py模块使用_.mp4 [268.3 MB]
13.xpath轴介绍_.mp4 [50.5 MB]
7.正则表达式规则(四)_.mp4 [161.6 MB]
12.xpath规则与运用介绍_.mp4 [161.2 MB]
📁 08_爬虫技术架构实战之京东爬虫
📁 02分类数据抓取
06_保存分类数据_.mp4 [45.2 MB]
05_创建分类爬虫抓取数据_.mp4 [154.2 MB]
04_确定分类信息的URL_.mp4 [20.8 MB]
📁 01需求与实现步骤
03_定义数据模型明确抓取的数据_.mp4 [40.8 MB]
02_京东全网爬虫实现步骤(1)_.mp4 [28.8 MB]
01_需求与技术选择_.mp4 [30.9 MB]
📁 03反爬及总结
16_QQ实现下载器中间件_.mp4 [72.3 MB]
17_QQ京东全网爬虫总结_.mp4 [20.9 MB]
📁 07_爬虫技术架构及实战
📁 06总结
1.课程总结_.mp4 [130.0 MB]
📁 05项目实战-豆瓣爬虫改造
6.案例-doubanbook爬虫改造(六)_.pcwlenv [83.0 MB]
4.案例-doubanbook爬虫改造(四)_.pcwlenv [47.2 MB]
5.案例-doubanbook爬虫改造(五)_.pcwlenv [80.2 MB]
3.案例-doubanbook爬虫改造(三)_.pcwlenv [79.6 MB]
1.案例-doubanbook爬虫改造(一)_.pcwlenv [66.9 MB]
2.案例-doubanbook爬虫改造(二)_.pcwlenv [66.1 MB]
📁 03爬虫系统与架构组件介绍
3.爬虫系统架构组件介绍(二)_.mp4 [83.9 MB]
1.爬虫系统架构组件整体掌握_.mp4 [63.5 MB]
6.爬虫系统架构组件介绍(五)_.mp4 [76.5 MB]
5.爬虫系统架构组件介绍(四)_.mp4 [158.3 MB]
4.爬虫系统架构组件介绍(三)_.mp4 [119.2 MB]
2.爬虫系统架构组件介绍(一)_.mp4 [135.1 MB]
📁 02爬虫系统与架构介绍
7.爬虫系统架构设计方案1优化策略(二)_.mp4 [163.7 MB]
9.爬虫系统架构设计方案1优化策略(四)_.mp4 [128.7 MB]
10.爬虫系统架构设计方案2简介_.mp4 [82.9 MB]
8.爬虫系统架构设计方案1优化策略(三)_.mp4 [96.4 MB]
2.为什么要自行实现一个爬虫系统架构_.mp4 [158.4 MB]
6.爬虫系统架构设计方案1优化策略(一)_.mp4 [107.5 MB]
3.爬虫系统架构中需要实现的主要爬虫业务_.mp4 [215.3 MB]
1.爬虫系统架构概念介绍_.mp4 [169.1 MB]
5.爬虫系统架构设计方案1内部逻辑_.mp4 [108.9 MB]
4.爬虫系统架构设计方案1_.mp4 [153.0 MB]
11.爬虫系统架构介绍小结_.mp4 [43.6 MB]
📁 01课程内容和系统环境介绍
1.课程内容与系统环境介绍_.mp4 [76.7 MB]
📁 04爬虫系统与架构方案设计实现
5.爬虫逻辑与基类实现_.mp4 [167.1 MB]
24.日志模块的简单使用_.mp4 [150.8 MB]
33.logstash数据过滤与定向输出(二)_.mp4 [84.3 MB]
19.Selenium与Chrome-Headless并发下载(一)_.mp4 [243.7 MB]
18.丢失请求与失败请求的捕获(四)_.mp4 [261.5 MB]
10.异步并发代码实现_.mp4 [316.7 MB]
6.主逻辑实现(一)_.mp4 [383.2 MB]
20.Selenium与Chrome-Headless并发下载(二)_.mp4 [177.5 MB]
23.日志收集和监控的必要性_.mp4 [116.6 MB]
15.丢失请求与失败请求的捕获(一)_.mp4 [242.8 MB]
22.模块安装_.mp4 [264.0 MB]
29.logstash向kafka生成日志数据(一)_.mp4 [207.8 MB]
12.基础策略代码实现优化_.mp4 [101.8 MB]
11.异步并发代码改造优化_.mp4 [159.6 MB]
1.爬虫系统架构实现与request_manager回顾_.mp4 [194.4 MB]
13.使用布隆过滤器进行请求过滤(一)_.mp4 [102.9 MB]
14.使用布隆过滤器进行请求过滤(二)_.mp4 [102.4 MB]
4.下载器对象实现_.mp4 [200.8 MB]
26.Logstash的工作原理_.mp4 [215.5 MB]
28.ELK启动运行(二)_.mp4 [218.5 MB]
32.logstash数据过滤与定向输出(一)_.mp4 [62.9 MB]
16.丢失请求与失败请求的捕获(二)_.mp4 [225.2 MB]
30.logstash向kafka生成日志数据(二)_.mp4 [101.4 MB]
9.新增下载器组件实现请求发出_.mp4 [214.6 MB]
21.Selenium与Chrome-Headless并发下载(三)_.mp4 [346.7 MB]
8.代码运行测试_.mp4 [247.4 MB]
17.丢失请求与失败请求的捕获(三)_.mp4 [187.2 MB]
34.将日志发送到微信实现警报_.mp4 [242.6 MB]
27.ELK启动运行(一)_.mp4 [212.1 MB]
2.基础策略实现代码结构介绍_.mp4 [74.3 MB]
3.Request对象和Response对象实现_.mp4 [229.5 MB]
31.logstash向kafka生成日志数据(三)_.mp4 [44.8 MB]
📁 02_Python爬虫开发环境与Docker
📁 02Python开发与Docker
9.Pycharm中docker-compose-file的配置与使用_.mp4 [37.7 MB]
6.配置代码自动上传与运行(一)_.mp4 [53.1 MB]
8.Pycharm中Dockerfile的配置与使用_.mp4 [73.6 MB]
5.配置远程Docker的镜像作为Pycharm的python解释器_.mp4 [62.2 MB]
3.Pycharm与Docker开发思路和原理_.mp4 [23.8 MB]
2.系统环境介绍_.mp4 [27.8 MB]
7.配置代码自动上传与运行(二)_.mp4 [52.9 MB]
4.Pycharm中配置Docker-Daemon的连接_.mp4 [68.0 MB]
📁 01课程介绍
1.Python爬虫开发环境与Docker课程介绍_.mp4 [102.1 MB]
📁 05WebSocket协议与爬虫
29.WebSocket协议介绍_.mp4 [32.5 MB]
30WebSocket客户端工具使用介绍与总结_.mp4 [84.3 MB]
📁 04数据抓包与环境配置
26.利用Charles配置PC端web抓包_.mp4 [81.7 MB]
28.数据抓包小结_.mp4 [6.4 MB]
25.数据抓包介绍_.mp4 [68.8 MB]
27.利用Charles配置移动端app抓包_.mp4 [80.2 MB]
📁 03HTTP、HTTPS协议与爬虫
18.Docker中selenium与chrome爬虫开发环境搭建与使用(四)_.mp4 [98.2 MB]
19.Docker中appium与android爬虫开发环境搭建与使用(一)_.mp4 [70.1 MB]
20.Docker中appium与android爬虫开发环境搭建与使用(二)_.mp4 [100.7 MB]
24.爬虫开发环境搭建小结_.mp4 [17.6 MB]
21.Docker中appium与android爬虫开发环境搭建与使用(三)_.mp4 [29.4 MB]
10.HTTP协议基本原理介绍_.mp4 [93.5 MB]
15.Docker中selenium与chrome爬虫开发环境搭建与使用(一)_.mp4 [100.0 MB]
13.利用Dockerfile配置安装Python环境(一)_.mp4 [79.4 MB]
23.Docker中appium与android爬虫开发环境搭建与使用(五)_.mp4 [58.2 MB]
16.Docker中selenium与chrome爬虫开发环境搭建与使用(二)_.mp4 [114.1 MB]
14.利用Dockerfile配置安装Python环境(二)_.mp4 [67.6 MB]
12.Python中HTTP？HTTPS相关模块介绍_.mp4 [89.3 MB]
22.Docker中appium与android爬虫开发环境搭建与使用(四)_.mp4 [37.3 MB]
17.Docker中selenium与chrome爬虫开发环境搭建与使用(三)_.mp4 [135.2 MB]
11.HTTPS协议基本原理介绍_.mp4 [47.5 MB]
📁 03_爬虫数据去重方案
📁 01课程介绍
1.爬虫中的去重处理课程介绍_.mp4 [25.7 MB]
📁 04基于simhash算法的去重
15.simhash算法去重方案及其应用场景介绍_.mp4 [65.3 MB]
17.simhash模块使用(一)_.mp4 [146.4 MB]
18.simhash模块使用(二)_.mp4 [251.9 MB]
16.基于simhash算法的去重原理_.mp4 [89.4 MB]
📁 06总结
26.总结_.mp4 [65.4 MB]
📁 02去重应用场景及其基本原理
5.判断依据之原始数据与原始数据特征_.mp4 [137.6 MB]
2.爬虫中的去重应用场景_.mp4 [48.3 MB]
4.去重原理之去重容器_.mp4 [206.3 MB]
3.去重原理之判断依据_.mp4 [172.0 MB]
6.去重容器类型介绍_.mp4 [143.5 MB]
📁 05布隆过滤器原理与实现
24.redis版布隆过滤器实现之hash表的原理_.mp4 [68.5 MB]
23.redis版布隆过滤器实现之计算多个hash值_.mp4 [206.0 MB]
22.pybloom模块介绍_.mp4 [61.0 MB]
21.布隆过滤器实现原理补充_.mp4 [65.6 MB]
25.redis版布隆过滤器实现之模块封装_.mp4 [311.0 MB]
20.布隆过滤器实现原理_.mp4 [209.9 MB]
19.布隆过滤器介绍_.mp4 [38.8 MB]
📁 03基于信息摘要算法的去重
12.实现并测试基于redis中无序集合的去重过滤器_.mp4 [300.2 MB]
9.去重过滤器基类实现_.mp4 [411.8 MB]
7.信息摘要算法介绍_.mp4 [216.3 MB]
14.优化基于mysql实现的去重过滤器_.mp4 [146.8 MB]
13.实现并测试基于mysql的去重过滤器_.mp4 [421.9 MB]
10.实现基于python中set的去重过滤器_.mp4 [117.1 MB]
11.测试基于python中set的去重过滤器_.mp4 [106.2 MB]
8.信息摘要算法实现方案介绍_.mp4 [62.6 MB]
📁 12-WEB方向
📁 02_RPC原理与实践（二）——分布式RPC
📁 01分布式RPC课程知识内容说明
01分布式RPC课程知识内容说明-.mp4 [1.8 MB]
📁 05kazoo使用
054_获取节点数据-.mp4 [5.8 MB]
051_kazoo简介与安装-.mp4 [2.9 MB]
053_创建节点-.mp4 [12.2 MB]
052_客户端连接-.mp4 [3.5 MB]
📁 04ZooKeeper安装
04_ZooKeeper安装-.mp4 [38.4 MB]
📁 06RPC服务器程序改写
062_服务器程序改写实现-.mp4 [19.9 MB]
061_保存在zookeeper节点层次和类型的设计确定-.mp4 [9.5 MB]
📁 02分布式系统基础知识
021_单机部署的缺点和多台服务器分布式的好处-.mp4 [7.3 MB]
022_分布式系统需要解决的问题与解决方案-.mp4 [9.8 MB]
📁 07RPC客户端程序改写
072_客户端程序实现1-.mp4 [15.9 MB]
072_客户端程序实现2-.mp4 [7.8 MB]
073_测试分布式RPC-.mp4 [7.1 MB]
071_客户端程序改写思路-.mp4 [7.9 MB]
📁 03认识ZooKeeper
031_ZooKeeper简介-.mp4 [14.7 MB]
032_ZooKeeper概念说明-.mp4 [28.6 MB]
📁 07_OpenStack云计算之综合实践
📁 05OpenStack综合实践之总结
093_OpenStack综合实践之总结-.mp4 [20.9 MB]
📁 04OpenStack综合实践之深入理解VM
087_OpenStack综合实践之深入理解VM(属性获取-元数据+获取)-.mp4 [25.3 MB]
086_OpenStack综合实践之深入理解VM(VM实例-配置文件)-.mp4 [20.3 MB]
090_OpenStack综合实践之深入理解VM(流程详解-第2阶段)-.mp4 [30.3 MB]
085_OpenStack综合实践之深入理解VM(VM实例-实例文件)-.mp4 [32.9 MB]
091_OpenStack综合实践之深入理解VM(流程详解-梳理)-.mp4 [40.1 MB]
089_OpenStack综合实践之深入理解VM(流程详解-第1阶段)-.mp4 [23.8 MB]
084_OpenStack综合实践之深入理解VM(如何通网)-.mp4 [17.6 MB]
092_OpenStack综合实践之深入理解VM(小结)-.mp4 [26.9 MB]
📁 01OpenStack综合实践之VM创建
057_OpenStack综合实践之VM创建(常见报错2)-.mp4 [22.1 MB]
058_OpenStack综合实践之VM创建(常见报错3)-.mp4 [30.3 MB]
059_OpenStack综合实践之VM创建(排错思路)-.mp4 [19.3 MB]
055_OpenStack综合实践之VM创建(创建实例-创建+检查)-.mp4 [29.0 MB]
054_OpenStack综合实践之VM创建(创建实例-秘钥+安全组+检查)-.mp4 [20.8 MB]
060_OpenStack综合实践之VM创建(小结)-.mp4 [16.1 MB]
053_OpenStack综合实践之VM创建(实例属性-网络+子网+实例)-.mp4 [31.0 MB]
056_OpenStack综合实践之VM创建(常见报错1)-.mp4 [30.2 MB]
📁 02OpenStack综合实践之可视化界面
066_OpenStack综合实践之可视化界面(管理员界面-身份管理+梳理)-.mp4 [18.6 MB]
065_OpenStack综合实践之可视化界面(管理员界面-管理员)-.mp4 [22.3 MB]
064_OpenStack综合实践之可视化界面(管理员界面-项目)-.mp4 [26.7 MB]
068_OpenStack综合实践之可视化界面(小结)-.mp4 [12.0 MB]
067_OpenStack综合实践之可视化界面(操作员界面)-.mp4 [10.4 MB]
062_OpenStack综合实践之可视化界面(部署-软件+配置)-.mp4 [34.1 MB]
063_OpenStack综合实践之可视化界面(部署-效果+梳理)-.mp4 [12.9 MB]
061_OpenStack综合实践之可视化界面(简介)-.mp4 [15.5 MB]
📁 03OpenStack综合实践之块存储部署
070_OpenStack综合实践之块存储部署(组件详解-流程+组件+场景)-.mp4 [24.1 MB]
082_OpenStack综合实践之块存储部署(多存储实践-命令行+可视化界面)-.mp4 [27.2 MB]
075_OpenStack综合实践之块存储部署(存储服务部署-效果+梳理)-.mp4 [14.1 MB]
072_OpenStack综合实践之块存储部署(控制服务部署-配置2+数据同步+权限+效果)-.mp4 [38.0 MB]
078_OpenStack综合实践之块存储部署(nfs存储部署-流程+磁盘+nfs)-.mp4 [14.9 MB]
076_OpenStack综合实践之块存储部署(存储实践-创建+附加)-.mp4 [24.8 MB]
081_OpenStack综合实践之块存储部署(多存储部署-准备+多存储配置+前后端绑定)-.mp4 [29.2 MB]
077_OpenStack综合实践之块存储部署(存储实践-卸载+删除+梳理)-.mp4 [26.3 MB]
071_OpenStack综合实践之块存储部署(控制服务部署-数据库+软件+配置)-.mp4 [25.1 MB]
073_OpenStack综合实践之块存储部署(存储服务部署-磁盘+lvm配置)-.mp4 [25.6 MB]
069_OpenStack综合实践之块存储部署(简介-官方+存储+cinder)-.mp4 [25.9 MB]
083_OpenStack综合实践之块存储部署(总结)-.mp4 [36.0 MB]
080_OpenStack综合实践之块存储部署(nfs存储部署-实践+梳理)-.mp4 [16.0 MB]
074_OpenStack综合实践之块存储部署(存储服务部署-软件+配置)-.mp4 [28.1 MB]
079_OpenStack综合实践之块存储部署(nfs存储部署-nfs后端+效果)-.mp4 [29.0 MB]
📁 12_Web与配置管理ansible
📁 04Ansible 快速入门之常用模块
024_快速入门之常用模块(系统模块1)-.mp4 [46.7 MB]
027_快速入门之常用模块(系统模块4)-.mp4 [23.1 MB]
033_快速入门之常用模块(系列命令1)-.mp4 [44.7 MB]
022_快速入门之常用模块(日常模块1)-.mp4 [41.9 MB]
035_快速入门之常用模块(系列命令3)-.mp4 [16.5 MB]
029_快速入门之常用模块(文件模块2)-.mp4 [24.5 MB]
030_快速入门之常用模块(文件模块3)-.mp4 [29.6 MB]
028_快速入门之常用模块(文件模块1)-.mp4 [35.4 MB]
026_快速入门之常用模块(系统模块3)-.mp4 [33.2 MB]
032_快速入门之常用模块(应用模块2)-.mp4 [34.5 MB]
023_快速入门之常用模块(日常模块2)-.mp4 [33.7 MB]
034_快速入门之常用模块(系列命令2)-.mp4 [35.4 MB]
025_快速入门之常用模块(系统模块2)-.mp4 [29.9 MB]
📁 08Ansible 进阶之Role
066_ansible进阶之Role(角色基础)-.mp4 [28.1 MB]
074_ansible进阶之Role(扩展功能3)-.mp4 [14.8 MB]
069_ansible进阶之Role(简单案例3)-.mp4 [17.2 MB]
071_ansible进阶之Role(角色管理)-.mp4 [36.3 MB]
067_ansible进阶之Role(简单案例1)-.mp4 [29.0 MB]
070_ansible进阶之Role(role结构)-.mp4 [16.3 MB]
079_第四天总结-.mp4 [24.8 MB]
078_ansible进阶之Role(综合实践4)-.mp4 [36.9 MB]
076_ansible进阶之Role(综合实践2)-.mp4 [40.8 MB]
073_ansible进阶之Role(扩展功能2)-.mp4 [46.4 MB]
075_ansible进阶之Role(综合实践)-.mp4 [20.6 MB]
077_ansible进阶之Role(综合实践3)-.mp4 [38.0 MB]
072_ansible进阶之Role(扩展功能1)-.mp4 [22.1 MB]
068_ansible进阶之Role(简单案例2)-.mp4 [47.9 MB]
📁 05Ansible 快速入门之playbook
040_快速入门之playbook(基础属性2)-.mp4 [23.5 MB]
036_快速入门之playbook(基础)-.mp4 [23.6 MB]
047_快速入门之playbook(标签2)-.mp4 [41.4 MB]
039_快速入门之playbook(基础属性1)-.mp4 [55.3 MB]
041_快速入门之playbook(基础属性3)-.mp4 [35.5 MB]
044_快速入门之playbook(任务依赖1)-.mp4 [29.2 MB]
038_第二天总结-.mp4 [28.6 MB]
042_快速入门之playbook(基础属性4)-.mp4 [23.1 MB]
045_快速入门之playbook(任务依赖2)-.mp4 [29.9 MB]
046_快速入门之playbook(标签1)-.mp4 [28.7 MB]
043_快速入门之playbook(异常中断)-.mp4 [46.6 MB]
037_快速入门之playbook(YAML详解)-.mp4 [50.8 MB]
📁 02Ansible 快速入门之基础知识
007_快速入门之基础知识(简介+功能简介)-.mp4 [29.8 MB]
📁 06Ansible 进阶之变量进阶
051_ansible进阶之变量进阶(变量-命令行)-.mp4 [27.7 MB]
052_ansible进阶之变量进阶(变量-playbook)-.mp4 [21.1 MB]
049_ansible进阶之变量进阶(变量-主机属性)-.mp4 [29.7 MB]
053_ansible进阶之变量进阶(变量-专用文件)-.mp4 [31.0 MB]
050_ansible进阶之变量进阶(变量-主机列表)-.mp4 [41.3 MB]
048_ansible进阶之变量进阶(变量基础)-.mp4 [24.0 MB]
📁 01项目管理基础
002_项目管理基础之项目环境(平台环境)-.mp4 [32.8 MB]
001_项目管理基础之项目环境(项目基础)-.mp4 [42.7 MB]
006_项目管理基础之项目管理(工具模式)-.mp4 [21.9 MB]
003_项目管理基础之项目环境(项目环境)-.mp4 [14.5 MB]
005_项目管理基础之项目管理(管理工具)-.mp4 [13.1 MB]
000_课程概况-.mp4 [6.7 MB]
004_项目管理基础之项目管理(管理方式)-.mp4 [26.7 MB]
📁 03Ansible 快速入门之软件部署
009_快速入门之软件部署(部署简介+准备工作2)-.mp4 [17.8 MB]
013_快速入门之软件部署(主机清单1)-.mp4 [42.5 MB]
012_快速入门之软件部署(简单使用2)-.mp4 [32.6 MB]
015_快速入门之软件部署(原理详解)-.mp4 [29.7 MB]
014_快速入门之软件部署(主机清单2)-.mp4 [29.5 MB]
008_快速入门之软件部署(部署简介+准备工作1)-.mp4 [31.4 MB]
021_快速入门之软件部署(命令执行过程)-.mp4 [30.7 MB]
016_快速入门之软件部署(配置详解)-.mp4 [45.6 MB]
017_快速入门之软件部署(简单实践1)-.mp4 [32.5 MB]
018_快速入门之软件部署(简单实践2)-.mp4 [33.2 MB]
010_快速入门之软件部署(软件安装)-.mp4 [15.6 MB]
020_快速入门之软件部署(主机进阶实践)-.mp4 [48.3 MB]
011_快速入门之软件部署(简单使用1)-.mp4 [41.8 MB]
📁 07Ansible 进阶之模板
059_ansible进阶之模板(迭代)-.mp4 [30.2 MB]
062_ansible进阶之模板(流程基础1)-.mp4 [17.4 MB]
055_ansible进阶之模板(快速入门)-.mp4 [45.0 MB]
056_ansible进阶之模板(条件1)-.mp4 [44.3 MB]
057_ansible进阶之模板(条件2)-.mp4 [27.5 MB]
060_ansible进阶之模板(迭代进阶1)-.mp4 [21.8 MB]
058_第三天总结-.mp4 [22.9 MB]
063_ansible进阶之模板(if流程)-.mp4 [40.7 MB]
054_ansible进阶之模板(模板基础)-.mp4 [24.4 MB]
061_ansible进阶之模板(迭代进阶2)-.mp4 [37.9 MB]
064_ansible进阶之模板(for流程1)-.mp4 [19.1 MB]
065_ansible进阶之模板(for流程2)-.mp4 [34.0 MB]
📁 11_Web与负载均衡LVS
📁 01集群简介
002_集群基础之集群简介(集群类型-实现方式)-.mp4 [28.1 MB]
001_集群基础之集群简介(集群基础-场景需求+解决方案+访问流程)-.mp4 [25.0 MB]
003_集群基础之集群简介(小结)-.mp4 [6.2 MB]
000_课程概况-.mp4 [4.4 MB]
📁 07TUN实践
041_lvs快速入门之TUN实践(简单实践2)-.mp4 [28.7 MB]
039_lvs快速入门之TUN实践(TUN简介)-.mp4 [16.8 MB]
043_lvs快速入门之TUN实践(原理详解)-.mp4 [22.8 MB]
042_lvs快速入门之TUN实践(简单实践3)-.mp4 [27.0 MB]
037_lvs快速入门之TUN实践(前置知识2)-.mp4 [9.9 MB]
044_lvs快速入门之小结-.mp4 [20.9 MB]
038_lvs快速入门之TUN实践(隧道实践)-.mp4 [51.3 MB]
036_lvs快速入门之TUN实践(前置知识)-.mp4 [30.3 MB]
📁 02LVS基础
004_lvs快速入门之lvs基础(防火墙回顾-五表五链+应用场景+地址转换)-.mp4 [23.6 MB]
005_lvs快速入门之lvs基础(简介-结构)-.mp4 [55.2 MB]
📁 04NAT实践
011_lvs快速入门之NAT实践(前置知识-网络设备+基本环境)-.mp4 [25.6 MB]
019_lvs快速入门之NAT实践(进阶实践1-实践小结+数据包分析)-.mp4 [25.2 MB]
016_lvs快速入门之NAT实践(原理详解-流程详解+数据包详解+请求流程)-.mp4 [27.9 MB]
023_lvs快速入门之NAT实践(小结)-.mp4 [20.2 MB]
017_lvs快速入门之NAT实践(应用技巧-原理技巧+应用技巧)-.mp4 [30.0 MB]
021_lvs快速入门之NAT实践(进阶实践2-https实践)-.mp4 [27.3 MB]
018_lvs快速入门之NAT实践(进阶实践-场景需求+需求分析+关键点分析+实践)-.mp4 [34.3 MB]
012_lvs快速入门之NAT实践(NAT简介-模型简介+模型分析)-.mp4 [23.3 MB]
014_lvs快速入门之NAT实践(简单实践-案例需求+基础环境设置)-.mp4 [21.5 MB]
020_lvs快速入门之NAT实践(进阶实践2-场景需求+需求分析+关键点分析+实践)-.mp4 [23.0 MB]
013_lvs快速入门之NAT实践(简单实践-案例需求+需求分析+关键点分析)-.mp4 [24.3 MB]
022_lvs快速入门之NAT实践(进阶实践2-集群实践+小结)-.mp4 [12.1 MB]
015_lvs快速入门之NAT实践(简单实践-web服务+lvs集群设置)-.mp4 [31.5 MB]
📁 06DR实践
029_lvs快速入门之DR实践(DR模型-模型简介+模型分析)-.mp4 [20.0 MB]
035_lvs快速入门之DR实践(应用技巧)-.mp4 [24.3 MB]
034_lvs快速入门之DR实践(原理详解)-.mp4 [16.0 MB]
028_lvs快速入门之DR实践(前置知识-ARP表+交换机原理+地址冲突)-.mp4 [38.4 MB]
032_lvs快速入门之DR实践(简单实践-案例实践2)-.mp4 [25.8 MB]
031_lvs快速入门之DR实践(简单实践-案例实践1)-.mp4 [34.1 MB]
033_lvs快速入门之DR实践(简单实践-案例实践3)-.mp4 [13.8 MB]
030_lvs快速入门之DR实践(简单实践-案例需求+需求分析+技术点分析)-.mp4 [20.2 MB]
📁 05调度策略
024_lvs快速入门之调度策略(前置知识-代理+会话+hash)-.mp4 [26.8 MB]
025_lvs快速入门之调度策略(调度基础+静态方法+动态方法)-.mp4 [35.0 MB]
027_lvs快速入门之调度策略(sh实践)-.mp4 [12.8 MB]
026_lvs快速入门之调度策略(wrr实践)-.mp4 [18.3 MB]
📁 03LVS快速入门
006_lvs快速入门之lvs快速入门(安装软件-命令简介)-.mp4 [30.1 MB]
008_lvs快速入门之lvs快速入门(主机命令-查看+增加+编辑+删除)-.mp4 [37.2 MB]
009_lvs快速入门之lvs快速入门(规则命令-保存+清空+载入+服务)-.mp4 [45.5 MB]
007_lvs快速入门之lvs快速入门(集群命令-查看+增加+编辑+删除)-.mp4 [26.8 MB]
010_lvs快速入门之lvs快速入门(小结)-.mp4 [13.5 MB]
📁 06_OpenStack云计算之环境部署
📁 05OpenStack部署之计算组件
036_OpenStack部署之计算组件(控制组件部署-数据库+软件安装+配置修改1)-.mp4 [50.1 MB]
039_OpenStack部署之计算组件(计算组件部署-软件+配置修改+启动)-.mp4 [38.6 MB]
041_OpenStack部署之计算组件(小结)-.mp4 [30.7 MB]
038_OpenStack部署之计算组件(控制组件部署-权限配置+效果查看)-.mp4 [34.5 MB]
035_OpenStack部署之计算组件(组件详解-权重+梳理)-.mp4 [32.1 MB]
040_OpenStack部署之计算组件(计算组件部署-效果查看)-.mp4 [22.7 MB]
034_OpenStack部署之计算组件(组件详解-官方+原理+组件)-.mp4 [36.5 MB]
📁 03OpenStack部署之认证组件
027_OpenStack部署之认证组件(部署梳理)-.mp4 [24.6 MB]
024_OpenStack部署之认证组件(组件部署-数据库配置+软件安装+软件配置+数据同步)-.mp4 [32.7 MB]
023_OpenStack部署之认证组件(组件详解-官方介绍+功能+核心术语+配置)-.mp4 [34.1 MB]
025_OpenStack部署之认证组件(组件部署-admin权限+http配置+权限配置1)-.mp4 [27.9 MB]
028_OpenStack部署之认证组件(总结)-.mp4 [26.5 MB]
026_OpenStack部署之认证组件(组件部署-权限配置2+认证效果)-.mp4 [35.5 MB]
📁 02OpenStack部署之支撑性服务
021_OpenStack部署之支撑性服务(memcache-作用+官方介绍+软件+配置)-.mp4 [15.5 MB]
019_OpenStack部署之支撑性服务(数据库-官方介绍+软件+配置+初始化)-.mp4 [27.3 MB]
022_OpenStack部署之支撑性服务(小结)-.mp4 [6.9 MB]
020_OpenStack部署之支撑性服务(rabbitmq-作用+官方介绍+软件+配置+插件)-.mp4 [37.9 MB]
📁 04OpenStack部署之镜像组件
031_OpenStack部署之镜像组件(组件部署-初始化+权限配置)-.mp4 [38.1 MB]
029_OpenStack部署之镜像组件(组件详解-官方+详解+存储+简介+配置)-.mp4 [39.1 MB]
033_OpenStack部署之镜像组件(小结)-.mp4 [22.5 MB]
030_OpenStack部署之镜像组件(组件部署-数据库配置+软件安装+软件配置)-.mp4 [36.3 MB]
032_OpenStack部署之镜像组件(效果查看)-.mp4 [31.4 MB]
📁 01OpenStack部署之实验环境
017_OpenStack部署之实验环境(基本环境-软件+时间同步+计算节点)-.mp4 [43.7 MB]
014_OpenStack部署之实验环境(准备工作-Centos7安装)-.mp4 [30.1 MB]
016_OpenStack部署之实验环境(准备工作-网络配置+安全配置+主机名配置)-.mp4 [34.1 MB]
015_OpenStack部署之实验环境(准备工作-ip设置+软件源)-.mp4 [31.2 MB]
018_OpenStack部署之实验环境(小结)-.mp4 [14.5 MB]
📁 06OpenStack部署之网络组件
051_OpenStack部署之网络组件(小结)-.mp4 [25.0 MB]
049_OpenStack部署之网络组件(计算节点部署-软件+配置)-.mp4 [24.6 MB]
046_OpenStack部署之网络组件(控制节点部署-配置3+数据同步-.mp4 [18.1 MB]
045_OpenStack部署之网络组件(控制节点部署-配置2)-.mp4 [27.7 MB]
043_OpenStack部署之网络组件(组件介绍-官方+原理+组件)-.mp4 [25.2 MB]
050_OpenStack部署之网络组件(计算节点部署-效果查看+梳理)-.mp4 [14.7 MB]
048_OpenStack部署之网络组件(控制节点部署-梳理)-.mp4 [18.9 MB]
044_OpenStack部署之网络组件(控制节点部署-数据库+软件+配置1)-.mp4 [31.0 MB]
042_OpenStack部署之网络组件(网络简介-简介+功能+基本架构+类型)-.mp4 [33.6 MB]
047_OpenStack部署之网络组件(控制节点部署-权限配置+效果查看)-.mp4 [29.8 MB]
📁 07OpenStack部署之小结
052_OpenStack部署之(小结)-.mp4 [13.4 MB]
📁 04_RPC原理与实践（四）——gRPC
📁 06服务器与客户端程序编写
065_客户端流式RPC调用服务器与客户端实现-.mp4 [11.8 MB]
062_服务器启动代码实现-.mp4 [12.8 MB]
064_服务器流式RPC调用服务器与客户端实现-.mp4 [13.7 MB]
066_双向流式RPC调用服务器与客户端实现-.mp4 [13.7 MB]
063_客户端一元RPC调用实现-.mp4 [12.8 MB]
061_服务器一元RPC调用方法实现-.mp4 [15.1 MB]
📁 04ProtocolBuffers
043_接口服务定义语法-.mp4 [6.9 MB]
042_数据类型与消息类型的语法-.mp4 [15.7 MB]
041_ProtocolBuffers简介及文档结构和注释语法-.mp4 [8.2 MB]
📁 05案例接口定义与代码生成
052_案例接口定义2-.mp4 [7.4 MB]
053_编译代码生成与生成文件说明-.mp4 [10.8 MB]
051_案例接口定义1-.mp4 [13.0 MB]
📁 01gRPC框架课程知识介绍及gRPC简介架构和使用方法
01_第四部分gRPC框架课程知识介绍及gRPC简介架构和使用方法-.mp4 [6.9 MB]
📁 02HTTP2协议
021_HTTP1协议的不足-.mp4 [10.6 MB]
022_HTTP2协议介绍-.mp4 [21.5 MB]
📁 03gRPC接口类型
03_gRPC接口类型-.mp4 [6.5 MB]
📁 01_RPC原理与实践（一）——RPC原理
📁 07struct模块使用说明
07_struct模块使用说明-.mp4 [9.9 MB]
📁 02RFC原理课程内容说明
02_第一部分RPC原理课程内容说明-.mp4 [1.7 MB]
📁 10RPC完整实现
101_实现思路说明-.mp4 [3.4 MB]
107_RPC调用测试-.mp4 [8.5 MB]
103_ServerStub实现1-.mp4 [32.4 MB]
106_服务器与客户端调用案例实现-.mp4 [13.7 MB]
104_ServerStub实现2-.mp4 [30.6 MB]
105_Server补充实现-.mp4 [21.8 MB]
102_ClientStub实现-.mp4 [23.8 MB]
📁 09RPC传输控制实现
092_客户端传输工具实现-.mp4 [5.5 MB]
093_服务端传输工具实现-.mp4 [5.6 MB]
091_RPC传输协议说明-.mp4 [10.6 MB]
📁 03RPC介绍
032_RPC在广义和狭义上的理解及与HTTP的关系-.mp4 [11.5 MB]
033_RPC的优缺点-.mp4 [6.4 MB]
031_RPC简介背景和用途-.mp4 [10.3 MB]
📁 06RPC实现之消息协议设计
063_返回消息协议设计-.mp4 [7.5 MB]
062_调用请求消息协议设计-.mp4 [13.8 MB]
061_消息协议实现思路与divide调用参数确定-.mp4 [13.8 MB]
📁 08RPC实现之消息协议转换实现
089_消息协议实现总结-.mp4 [2.5 MB]
086_请求消息协议实现测试-.mp4 [13.0 MB]
087_返回值数据转换为消息数据的实现-.mp4 [15.0 MB]
081_请求参数转换为消息数据实现-.mp4 [22.6 MB]
088_消息数据转换为返回值数据的实现-.mp4 [10.0 MB]
083_请求消息数据转换为请求原始参数的实现2-.mp4 [22.7 MB]
084_args_decode方法修正与read_all方法实现-.mp4 [15.2 MB]
082_请求消息数据转换为请求原始参数的实现1-.mp4 [4.0 MB]
085_方法名协议实现-.mp4 [9.4 MB]
📁 11多线程RPC服务器实现
11_多线程RPC服务器实现-.mp4 [14.0 MB]
📁 04RPC结构和调用流程
04_RPC结构和调用流程-.mp4 [16.6 MB]
📁 05RPC消息协议
051_消息协议的说明-.mp4 [5.8 MB]
053_消息边界问题说明-.mp4 [14.2 MB]
054_消息内容和压缩问题-.mp4 [16.8 MB]
052_设计消息协议的目标-.mp4 [5.6 MB]
📁 01整体课程介绍
01_课程整体介绍及前置知识点说明-.mp4 [3.5 MB]
📁 03_RPC原理与实践（三）——Thrift
📁 08客户端案例程序编写
082_客户端调用编写与测试-.mp4 [11.8 MB]
081_客户端调用的工具创建-.mp4 [9.5 MB]
📁 03Thrift框架的实现技术架构
03_Thrift框架的实现技术架构-.mp4 [6.0 MB]
📁 04Thrift的安装
04_Thrift的安装-.mp4 [15.3 MB]
📁 06消息协议与传输的选择
06_消息协议与传输的选择-.mp4 [9.7 MB]
📁 01Thrift框架课程知识说明与Thrift简介
01_第三部分Thrift框架课程知识说明与Thrift简介-.mp4 [13.6 MB]
📁 02IDL接口定义语言说明与Thrift使用方法
02_IDL接口定义语言说明与Thrift使用方法-.mp4 [23.6 MB]
📁 07服务端案例程序编写
072_服务端接口服务方法实现-.mp4 [12.0 MB]
073_创建服务器开启RPC服务-.mp4 [15.4 MB]
071_服务端程序编写思路-.mp4 [7.9 MB]
📁 05Thrift接口定义语言
052_常量枚举结构体与异常类型-.mp4 [10.8 MB]
053_注释和服务定义-.mp4 [13.7 MB]
051_基本数据类型与容器类型-.mp4 [10.2 MB]
054_thrift编译器生成代码-.mp4 [11.8 MB]
📁 09_代码配置管理之流程&方案
📁 04版本控制
015_版本控制之总结-.mp4 [6.4 MB]
012_版本控制之简介(版本控制)-.mp4 [22.3 MB]
014_版本控制之种类(分类和工具)-.mp4 [29.1 MB]
013_版本控制之简介(版本控制作用)-.mp4 [23.7 MB]
📁 06开发模型
028_开发模型之边做边改-.mp4 [17.8 MB]
039_代码配置管理上篇总结-.mp4 [19.4 MB]
034_开发模型之敏捷模型1-.mp4 [40.2 MB]
029_开发模型之瀑布模型-.mp4 [36.0 MB]
031_开发模型之增量模型-.mp4 [33.1 MB]
037_开发模型之精益模型2-.mp4 [34.8 MB]
038_开发模型之总结-.mp4 [19.4 MB]
032_开发模型之快速原型模型-.mp4 [30.0 MB]
033_开发模型之螺旋模型-.mp4 [26.4 MB]
030_开发模型之迭代模型-.mp4 [29.7 MB]
035_开发模型之敏捷模型2-.mp4 [21.5 MB]
036_开发模型之精益模型1-.mp4 [31.8 MB]
📁 02绪论
001_绪论(强烈推荐观看,画好知识边界)-.mp4 [29.0 MB]
📁 03项目基础知识
002_项目基础知识之传统生命周期(调研-设计-开发)-.mp4 [23.7 MB]
009_项目基础知识之项目演变(企业中期四阶段)-.mp4 [40.0 MB]
004_项目基础知识之新型生命周期(项目阶段)-.mp4 [28.5 MB]
008_项目基础知识之项目演变(企业初期四阶段)-.mp4 [34.5 MB]
007_项目基础知识之项目演变(基本结构+开发框架演变)-.mp4 [31.9 MB]
010_项目基础知识之项目演变(企业中后期两阶段+小结)-.mp4 [21.8 MB]
005_项目基础知识之新型生命周期(常见术语)-.mp4 [24.3 MB]
011_项目基础知识之总结-.mp4 [18.8 MB]
006_项目基础知识之新型生命周期(周期效果+小结)-.mp4 [23.7 MB]
003_项目基础知识之传统生命周期(测试-运营)-.mp4 [23.5 MB]
📁 01课程简介
000_课程简介-.mp4 [4.5 MB]
📁 05分支管理
025_分支管理之主干开发(优秀案例)-.mp4 [20.2 MB]
020_分支管理之分支开发(分支发布)-.mp4 [30.9 MB]
027_分支管理之总结-.mp4 [18.2 MB]
017_分支管理之基础知识(分支概念)-.mp4 [34.6 MB]
024_分支管理之主干开发(主干发布)-.mp4 [33.7 MB]
019_分支管理之基础知识(小结)-.mp4 [10.9 MB]
026_分支管理之主干开发(小结)-.mp4 [9.9 MB]
018_分支管理之基础知识(分支开发流程)-.mp4 [28.9 MB]
021_分支管理之分支开发(主干发布)-.mp4 [39.1 MB]
022_分支管理之分支开发(小结)-.mp4 [6.1 MB]
023_分支管理之主干开发(分支发布)-.mp4 [33.2 MB]
016_分支管理之基础知识(常见术语)-.mp4 [31.4 MB]
📁 05_云计算基础之云计算概念+架构+特点
📁 08云计算基础之小结
008_云计算基础之小结-.mp4 [16.2 MB]
📁 004_云计算基础之基本概念(实现方式+现状+提供商)
004_云计算基础之基本概念(实现方式+现状+提供商)-.mp4 [28.2 MB]
📁 07云计算基础之虚拟化VS云计算
007_云计算基础之虚拟化&云计算(虚拟化+云计算+关系)-.pcwlenv [17.6 MB]
📁 02云计算基础之引言
002_云计算基础之引言(资源使用+资源管理+虚拟化+云计算+云计算历史)-.mp4 [40.5 MB]
📁 06云计算基础之基本架构
006_云计算基础之基本架构(基本架构+架构思考)-.mp4 [31.2 MB]
📁 01绪论
001_绪论(强烈建议观看-知识的边界)-.mp4 [26.0 MB]
📁 11OpenStack简介之组件介绍
011_OpenStack简介之组件介绍(组件简介+完美组件)-.mp4 [21.8 MB]
📁 03云计算基础之基本概念
003_云计算基础之基本概念(云计算概念+什么是云计算)-.mp4 [22.9 MB]
📁 09OpenStack简介
009_OpenStack简介之简介(历史+简介+核心服务+发行+使用标准)-.mp4 [36.1 MB]
📁 05云计算基础之常见种类
005_云计算基础之常见种类(云计算分类+衍生云+选用标准)-.mp4 [26.9 MB]
📁 12OpenStack简介之实验环境
012_OpenStack简介之实验环境(学习环境+主机环境)-.mp4 [26.3 MB]
📁 00课程介绍
000_课程简介-.mp4 [20.2 MB]
📁 10OpenStack简介之架构设计
010_OpenStack简介之架构设计(逻辑图+架构设计图+概念图)-.mp4 [32.9 MB]
📁 13OpenStack简介之小结
013_OpenStack简介之小结-.pcwlenv [22.4 MB]
📁 10_代码配置管理工具&实战
📁 Git篇
016_git快速入门之文件状态实践(状态实践)-.mp4 [33.4 MB]
010_git快速入门之环境初始化(命令简介+梳理)-.mp4 [37.3 MB]
048_git快速入门之标签管理(基础简介+日常命令)-.mp4 [45.7 MB]
013_git快速入门之数据结构(数据结构实践2+梳理)-.mp4 [22.8 MB]
051_git快速入门之标签管理(基本操作)-.mp4 [53.0 MB]
009_git快速入门之环境初始化(克隆仓库+命令补全)-.mp4 [37.5 MB]
026_git快速入门之文件级别撤销(撤销提交+撤销缓存)-.mp4 [34.5 MB]
023_git快速入门之增加&提交(补充技巧知识点)-.mp4 [25.8 MB]
017_git快速入门之文件状态实践(小结)-.mp4 [20.9 MB]
036_git快速入门之忽略实践(全局.gitignore)-.mp4 [18.5 MB]
032_git快速入门之对象级别撤销(reflog+check实践)-.mp4 [36.9 MB]
033_git快速入门之忽略基础(方法+原则+优先级)-.mp4 [45.1 MB]
005_git快速入门之git安装(简介+目录标准化+依赖软件)-.mp4 [39.9 MB]
030_git快速入门之对象级别撤销(reset实践)-.mp4 [31.2 MB]
006_git快速入门之git安装(源码方式安装)-.mp4 [30.4 MB]
007_git快速入门之git安装(windows安装+梳理)-.mp4 [30.1 MB]
031_git快速入门之对象级别撤销(revert实践)-.mp4 [31.5 MB]
053_git进阶之分支基础(前置知识)-.mp4 [15.8 MB]
000_课程简介(强烈推荐观看,画好知识边界)-.mp4 [24.3 MB]
015_git快速入门之文件状态(状态简介+状态详解)-.mp4 [18.2 MB]
050_git快速入门之标签管理(生成秘钥)-.mp4 [41.5 MB]
001_git快速入门之基础知识(版本控制回顾)-.mp4 [35.2 MB]
029_git快速入门之对象级别撤销(简介+reset原理)-.mp4 [27.4 MB]
038_git快速入门之基础操作(小结)-.mp4 [44.3 MB]
020_git快速入门之增加&提交(增加+提交+修改后提交)-.mp4 [43.8 MB]
041_git快速入门之git远程仓库(查看+创建)-.mp4 [43.0 MB]
043_git快速入门之git远程仓库部署(网络环境配置)-.mp4 [37.4 MB]
002_git快速入门之基础知识(git历史)-.mp4 [42.5 MB]
012_git快速入门之数据结构(数据结构实践1)-.mp4 [42.5 MB]
045_git快速入门之git远程仓库管理(添加+获取+提交)-.mp4 [34.1 MB]
042_git快速入门之git远程仓库部署(简介+基本环境)-.mp4 [22.5 MB]
021_git快速入门之文件区别(命令简介+4场景实践)-.mp4 [38.6 MB]
028_git快速入门之文件级别撤销(梳理)-.mp4 [31.7 MB]
052_git快速入门之标签管理(小结)-.mp4 [21.4 MB]
024_git快速入门之提交记录(简介+参数)-.mp4 [69.4 MB]
027_git快速入门之文件级别撤销(撤销修改)-.mp4 [39.9 MB]
008_git快速入门之环境初始化(初始化+配置实践)-.mp4 [46.7 MB]
011_git快速入门之数据结构(基本结构+对象数据库)-.mp4 [27.1 MB]
018_git快速入门之基础操作(区域操作简介)-.mp4 [31.5 MB]
044_git快速入门之git远程仓库部署(权限配置+测试)-.mp4 [31.4 MB]
019_git快速入门之基础操作(获取操作)-.mp4 [28.6 MB]
049_git快速入门之标签管理(认证标签简介+原理简介)-.mp4 [32.7 MB]
035_git快速入门之忽略实践(项目.gitignore)-.mp4 [24.6 MB]
034_git快速入门之忽略实践(exclude)-.mp4 [18.6 MB]
047_git快速入门之git远程仓库(小结)-.mp4 [15.2 MB]
046_git快速入门之git远程仓库管理(其他+梳理)-.mp4 [16.9 MB]
004_git快速入门之基础知识(小结)-.mp4 [13.0 MB]
003_git快速入门之基础知识(git生态)-.mp4 [18.4 MB]
022_git快速入门之删除&移动(2删除+2移动)-.mp4 [42.4 MB]
039_git快速入门之远程仓库简介(简介+分类+命令)-.mp4 [21.2 MB]
040_git快速入门之git远程仓库(简介+4种协议)-.mp4 [50.2 MB]
025_git快速入门之文件级别撤销(简介+撤销提交)-.mp4 [26.1 MB]
037_git快速入门之忽略实践(忽略失效)-.mp4 [30.5 MB]
014_git快速入门之区域管理(区域简介+区域设置)-.mp4 [23.7 MB]
📁 08_OpenStack云计算之实践拓展
📁 02OpenStack实践拓展之定制网络
109_OpenStack实践拓展之定制网络(定制双网络-双网络属性+测试)-.mp4 [24.9 MB]
107_OpenStack实践拓展之定制网络(定制双网络-双网卡环境)-.mp4 [25.7 MB]
106_OpenStack实践拓展之定制网络(双网络-需求+分析+方案)-.mp4 [19.1 MB]
108_OpenStack实践拓展之定制网络(定制双网络-配置修改+环境检查)-.mp4 [23.5 MB]
111_OpenStack实践拓展之定制网络(小结)-.mp4 [13.6 MB]
110_OpenStack实践拓展之定制网络(操作梳理)-.mp4 [16.2 MB]
📁 04OpenStack云计算课程总结
119_OpenStack云计算(入门篇-快速梳理)-.mp4 [38.2 MB]
120_OpenStack云计算(收尾)-.mp4 [7.9 MB]
📁 03OpenStack实践拓展之其他内容
112_OpenStack实践拓展之其他内容(防火墙规则)-.mp4 [15.6 MB]
116_OpenStack实践拓展之其他内容(增加计算节点-梳理)-.mp4 [21.6 MB]
114_OpenStack实践拓展之其他内容(增加计算节点-需求+环境+部署nova)-.mp4 [47.4 MB]
117_OpenStack实践拓展之其他内容(删除计算节点)-.mp4 [30.1 MB]
115_OpenStack实践拓展之其他内容(增加计算节点-部署neutron+测试)-.mp4 [37.8 MB]
113_OpenStack实践拓展之其他内容(主机名规则)-.mp4 [18.7 MB]
118_OpenStack实践拓展之其他内容(小结)-.mp4 [19.9 MB]
📁 01OpenStack实践拓展之定制映像
102_OpenStack实践拓展之定制映像(映像制作-其他功能+镜像压缩)-.mp4 [21.4 MB]
099_OpenStack实践拓展之定制映像(映像制作-脚本框架)-.mp4 [12.2 MB]
104_OpenStack实践拓展之定制映像(映像制作-效果查看+梳理)-.mp4 [13.3 MB]
096_OpenStack实践拓展之定制映像(映像制作-创建虚拟机)-.mp4 [24.3 MB]
100_OpenStack实践拓展之定制映像(映像制作-定制脚本1)-.mp4 [15.8 MB]
097_OpenStack实践拓展之定制映像(映像制作-虚拟机基本安全)-.mp4 [22.8 MB]
103_OpenStack实践拓展之定制映像(映像制作-创建vm)-.mp4 [21.1 MB]
105_OpenStack实践拓展之定制映像(小结)-.mp4 [16.9 MB]
094_OpenStack实践拓展之定制映像(映像简介)-.mp4 [16.9 MB]
095_OpenStack实践拓展之定制映像(映像制作-准备环境)-.mp4 [17.3 MB]
101_OpenStack实践拓展之定制映像(映像制作-定制脚本2)-.mp4 [27.5 MB]
📁 05阶段-项目测试和监控
📁 day05-Vue组件
📁 day05-Vue组件
📁 day03-DRF框架
📁 day03-DRF框架
📁 day01-DRF框架
📁 day01-DRF框架
📁 day04-DRF框架
📁 day04-DRF框架
📁 day02-DRF框架
📁 day02-DRF框架
📁 07-flask框架与项目
📁 day7_黑马头条项目
14总结.mp4 [12.8 MB]
03读写分离与事务隔离级别.mp4 [16.4 MB]
06项目目录说明1.mp4 [50.7 MB]
04Gitflow工作流和冲突说明.mp4 [30.1 MB]
05项目运行方式演示和说明.mp4 [52.0 MB]
01反馈说明和课程回顾.mp4 [26.3 MB]
13请求钩子提取用户id.mp4 [34.7 MB]
12生成token.mp4 [37.9 MB]
11用户登录代码说明.mp4 [25.8 MB]
07项目目录说明2.mp4 [20.0 MB]
08项目调试方法和tail命令.mp4 [15.9 MB]
02课程介绍.mp4 [16.1 MB]
📁 day09_黑马头条项目_第06天
02_缓存的背景.mp4 [35.0 MB]
11_用户个人信息缓存redis数据选型.mp4 [35.2 MB]
10_头条项目缓存设计.mp4 [28.6 MB]
01_复习.mp4 [37.2 MB]
05_缓存的数据保存形式.mp4 [30.8 MB]
08_缓存使用模式.mp4 [45.4 MB]
06_缓存数据的有效期原因.mp4 [14.1 MB]
07_缓存的有效期和淘汰策略.mp4 [68.3 MB]
15_扩展_加密算法说明1.mp4 [7.6 MB]
09_缓存穿透与缓存雪崩.mp4 [30.5 MB]
13_头条项目持久保存数据历史数据选型.mp4 [37.9 MB]
16_扩展_加密算法说明2.mp4 [11.4 MB]
03_缓存架构.mp4 [25.6 MB]
12_用户关注里诶包缓存redis数据选型.mp4 [30.8 MB]
14_头条项目持久保存数据统计数据选型.mp4 [17.9 MB]
04_缓存的数据内容.mp4 [48.8 MB]
📁 day8_黑马头条项目
02课程介绍.mp4 [11.3 MB]
07七牛云实现流程图.mp4 [20.9 MB]
12CDN介绍和Yapi接口管理平台.mp4 [24.4 MB]
13总结.mp4 [6.6 MB]
03登录验证装饰器.mp4 [39.5 MB]
11头像上传实现和测试.mp4 [73.5 MB]
05token的禁用说明.mp4 [27.0 MB]
10上传头像接口设计.mp4 [16.2 MB]
09七牛云工具测试.mp4 [36.0 MB]
06对象存储七牛云介绍.mp4 [22.7 MB]
08七牛云工具封装.mp4 [45.0 MB]
04token的刷新实现.mp4 [47.1 MB]
01反馈和课程回顾.mp4 [15.6 MB]
📁 13_黑马头条项目_第10天
11_socketio收发数据的方法.mp4 [29.1 MB]
14_头条项目聊天机器人编写.mp4 [36.0 MB]
17_头条项目关注消息通知推送业务说明.mp4 [20.0 MB]
15_send方法与测试工具的使用.mp4 [15.0 MB]
22_关于即时通讯的总结.mp4 [24.2 MB]
20_解决消息推送接收人身份的问题.mp4 [66.0 MB]
16_调整socketio代码结构与测试.mp4 [15.7 MB]
19_补充flask和socketio代码添加manager使用.mp4 [32.5 MB]
09_协程库原理.mp4 [24.0 MB]
13_使用命令行提取处理端口号.mp4 [11.7 MB]
05_websocket介绍.mp4 [44.5 MB]
21_用户关注消息通知推送测试.mp4 [36.3 MB]
10_协程方式运行socketio服务器的方式.mp4 [10.9 MB]
18_socketio提供的manager使用说明.mp4 [30.5 MB]
12_创建socketio服务器编写.mp4 [18.4 MB]
07_socketio服务器创建的方式.mp4 [22.2 MB]
01_复习.mp4 [21.9 MB]
02_即时通讯说明介绍.mp4 [25.6 MB]
04_利用长连接的comet方式说明.mp4 [32.6 MB]
08_协程介绍.mp4 [22.6 MB]
06_socketio介绍.mp4 [29.6 MB]
03_HTTP轮询机制说明.mp4 [22.8 MB]
📁 day3_黑马头条项目
09flask-restful响应处理marshal序列化数据.mp4 [24.1 MB]
08flask-restful请求处理location.mp4 [12.6 MB]
07flask-restful请求处理type.mp4 [26.7 MB]
10flask-restful响应处理定义json格式数据.mp4 [39.8 MB]
05flask-restful添加装饰器.mp4 [19.6 MB]
13pycharm配置远程解释器.mp4 [57.9 MB]
01反馈和课程回顾.mp4 [31.6 MB]
03flask-restful工具的基本使用.mp4 [20.4 MB]
04flask-restful蓝图使用.mp4 [19.7 MB]
12虚拟机的基本使用.mp4 [21.8 MB]
15总结.mp4 [9.6 MB]
02课程介绍.mp4 [20.3 MB]
11项目课程说明和学习目标.mp4 [23.1 MB]
14产品原型使用说明.mp4 [11.1 MB]
📁 day6_黑马头条项目
集群和分布式.mp4 [14.2 MB]
02课程介绍.mp4 [23.9 MB]
12redis数据高可用.mp4 [45.0 MB]
08数据库索引.mp4 [16.1 MB]
01反馈和课程回顾.mp4 [30.3 MB]
05主从复制和读写分离.mp4 [12.0 MB]
03复制集和分布式.mp4 [14.2 MB]
11redis持久化AOF和RDB.mp4 [40.7 MB]
10redis的事务和watch.mp4 [18.3 MB]
13总结.mp4 [21.4 MB]
07分布式id和雪花算法.mp4 [32.1 MB]
06分库分表.mp4 [37.3 MB]
04redis复制集和分布式说明.mp4 [17.4 MB]
09数据库优化.mp4 [16.6 MB]
📁 day2_黑马头条项目
02课程介绍.mp4 [27.1 MB]
03请求信息固定参数转换器.mp4 [35.7 MB]
04请求信息自定义转换器.mp4 [30.4 MB]
13用户身份验证g对象.mp4 [18.1 MB]
09状态保持cookie和session.mp4 [33.8 MB]
05请求信息request对象的使用.mp4 [45.1 MB]
08响应信息自定义状态码和响应头.mp4 [15.2 MB]
14手动开启上下文.mp4 [13.6 MB]
15总结.mp4 [6.7 MB]
07作业说明不使用装饰器实现路由映射.mp4 [11.9 MB]
11请求钩子.mp4 [23.3 MB]
10异常处理abort和errohandler.mp4 [22.7 MB]
06响应信息模板&重定向&json.mp4 [41.9 MB]
12上下文对象.mp4 [39.8 MB]
01课程回顾.mp4 [17.2 MB]
📁 15_黑马头条项目_第12天
06_单元测试中创建flask测试客户端.mp4 [28.6 MB]
09_supervisor使用.mp4 [65.0 MB]
08_gunicorn使用.mp4 [22.9 MB]
07_编写搜索接口的单元测试案例.mp4 [49.9 MB]
02_单元测试说明.mp4 [31.3 MB]
01_复习.mp4 [25.8 MB]
04_unittest使用.mp4 [14.7 MB]
05_flask编写单元测试客户端的使用.mp4 [37.7 MB]
10_每日反馈.mp4 [29.9 MB]
03_assert断言使用.mp4 [18.2 MB]
📁 11_黑马头条项目_第08天
03_定时任务的解决方式对比.mp4 [37.8 MB]
02_修正统计数据的需求分析.mp4 [50.4 MB]
04_apscheduler的调度器.mp4 [35.2 MB]
06_apscheduler的定时任务管理.mp4 [7.6 MB]
01_复习.mp4 [38.0 MB]
11_定时任务方法抽离复用编写2.mp4 [29.6 MB]
05_apscheduler的执行器与触发器.mp4 [22.9 MB]
09_解决定时任务重需要使用flask上下文对象的问题.mp4 [21.3 MB]
07_头条项目中定义调度器编写.mp4 [39.7 MB]
12_web系统与推荐系统调用需求分析.mp4 [27.7 MB]
10_定时任务方法抽离复用编写1.mp4 [35.7 MB]
08_定时修正统计数据的定时任务编写.mp4 [61.9 MB]
13_子系统调用方式说明.mp4 [21.4 MB]
📁 day01_黑马头条项目
08加载配置信息的三种方式.mp4 [71.4 MB]
06基本程序实现.mp4 [16.6 MB]
09run方法参数说明.mp4 [25.4 MB]
03Flask框架的基本介绍.mp4 [20.3 MB]
07程序参数name说明.mp4 [55.8 MB]
13总结.mp4 [8.8 MB]
02学习目标.mp4 [18.2 MB]
01课程介绍.mp4 [9.5 MB]
11路由说明和指定请求方法.mp4 [24.6 MB]
04框架对比和扩展包介绍.mp4 [26.7 MB]
05环境配置和依赖文件.mp4 [27.5 MB]
10开发服务器运行方式.mp4 [21.0 MB]
12蓝图.mp4 [43.3 MB]
📁 14_黑马头条项目_第11天
11_查询修改删除类型表.mp4 [30.6 MB]
15_es基本查询使用.mp4 [32.8 MB]
20_补全提示建议查询使用.mp4 [30.3 MB]
13_修改删除文档数据.mp4 [23.5 MB]
17_python使用es的库.mp4 [13.3 MB]
08_索引库操作.mp4 [18.7 MB]
18_头条项目用户文章搜索视图编写.mp4 [73.3 MB]
12_新增查询文档数据.mp4 [22.0 MB]
06_curl使用与查询集群状态.mp4 [21.7 MB]
09_类型表保存数据的确定.mp4 [26.4 MB]
19_拼写纠错建议查询使用.mp4 [23.9 MB]
02_elasticsearch说明.mp4 [29.0 MB]
22_数据库连接查询说明.mp4 [38.6 MB]
14_es数据导入与logstash使用.mp4 [99.1 MB]
07_ik中文分析器使用与测试.mp4 [11.7 MB]
04_分析_相关性计算和搜索原理总结.mp4 [34.4 MB]
05_es集群说明.mp4 [37.3 MB]
03_反向索引.mp4 [25.6 MB]
01_复习.mp4 [25.0 MB]
21_头条项目用户搜索输入提示补全业务实现.mp4 [42.5 MB]
16_es高级查询使用.mp4 [62.6 MB]
23_扩展_TCP三次握手四次挥手说明.mp4 [19.0 MB]
10_类型映射的创建.mp4 [47.0 MB]
📁 12_黑马头条项目_第09天
13_在头条flask项目中定义rpc客户端连接对象.mp4 [29.7 MB]
02_http与rpc的对比.mp4 [22.7 MB]
10_rpc服务器函数代码实现.mp4 [34.5 MB]
12_rpc的简易加法案例.mp4 [73.0 MB]
06_头条项目首页新闻推荐rpc接口文件编写.mp4 [48.3 MB]
09_rpc服务器编写.mp4 [39.8 MB]
11_rpc客户端编写.mp4 [35.9 MB]
07_protobuf语法说明.mp4 [28.6 MB]
01_复习与每日反馈.mp4 [63.4 MB]
05_头条项目首页新闻推荐rpc接口参数分析.mp4 [41.8 MB]
03_rpc的介绍说明.mp4 [41.4 MB]
14_头条项目首页文章列表视图编写.mp4 [94.6 MB]
04_gRPC介绍与使用方式说明.mp4 [59.4 MB]
08_rpc接口文件编译生成python代码.mp4 [29.3 MB]
📁 10_黑马头条项目_第07天
02_缓存工具类的封装设计思路.mp4 [45.5 MB]
01_复习.mp4 [23.9 MB]
10_用户个人页视图编写与测试.mp4 [59.0 MB]
09_用户个人信息缓存工具类清除缓存和判断用户存在方法编写.mp4 [30.8 MB]
06_用户个人信息缓存工具类查询代码编写2.mp4 [31.8 MB]
12_zincrby命令说明.mp4 [10.9 MB]
08_缓存工具类异常处理的编写.mp4 [43.8 MB]
13_统计工具类的抽象与继承编写.mp4 [23.7 MB]
07_缓存有效期工具类的编写.mp4 [42.9 MB]
11_统计数据持久保存工具类编写.mp4 [58.7 MB]
04_用户个人信息缓存工具类中方法设计.mp4 [17.3 MB]
03_用户个人信息缓存工具类中属性设计.mp4 [15.9 MB]
05_用户个人信息缓存工具类查询代码编写1.mp4 [42.2 MB]
📁 day4_黑马头条项目
04开发人员和周期说明.mp4 [23.3 MB]
01反馈和课程回顾.mp4 [24.8 MB]
03项目技术架构介绍.mp4 [17.7 MB]
02课程介绍.mp4 [11.4 MB]
11个人信息页.mp4 [37.6 MB]
06主键设计.mp4 [22.9 MB]
05开发平台gitlib说明和Yapi接口平台.mp4 [10.9 MB]
13数据库sql文件说明.mp4 [21.5 MB]
14总结.mp4 [13.7 MB]
09文章详情页面.mp4 [44.9 MB]
10范式和反范式.mp4 [14.7 MB]
12字段类型和索引设计.mp4 [42.4 MB]
08json类型存储图片.mp4 [17.8 MB]
07外键设计说明.mp4 [22.4 MB]
📁 day5_黑马头条项目
06SQLALchemy基本配置.mp4 [29.0 MB]
05SQLAlchemy介绍.mp4 [8.9 MB]
07SQLAlchemy的字段列选项关系选项.mp4 [23.3 MB]
02课程介绍.mp4 [6.5 MB]
12SQLAlchemy运算符与或非order_by&limit&offset&count&复合查询.mp4 [46.4 MB]
09SQLAlchemy添加数据.mp4 [19.7 MB]
03ORM的特点.mp4 [14.9 MB]
17总结.mp4 [10.8 MB]
14SQLAlchemy连接查询1.mp4 [54.6 MB]
13SQLAlchemy优化查询和聚合查询.mp4 [36.6 MB]
01课程回顾.mp4 [13.0 MB]
16SQLAlchemy更新删除事务.mp4 [17.4 MB]
15SQLAlchemy连接查询2.mp4 [80.4 MB]
08SQLAlchemy模型类定义和关系说明.mp4 [44.6 MB]
04ORM的用法说明.mp4 [9.6 MB]
📁 09-文学项目
📁 4_分类管理
01黑马文学-课程介绍_.mp4 [5.8 MB]
12黑马文学-热门搜索词补充说明_.mp4 [7.5 MB]
11黑马文学-热门搜索词步骤和代码实现_.mp4 [20.0 MB]
07黑马文学-分类书本列表获取参数_.mp4 [12.6 MB]
02黑马文学-分类列表实现步骤_.mp4 [7.4 MB]
05黑马文学-书籍分类列表接口设计分析_.mp4 [9.6 MB]
04黑马文学-分类列表测试_.mp4 [4.5 MB]
06黑马文学-书籍分类列表实现步骤_.mp4 [6.9 MB]
13黑马文学-总结_.mp4 [14.9 MB]
09黑马文学-分类书本列表分页查询返回数据_.mp4 [30.2 MB]
10黑马文学-分类书籍列表测试_.mp4 [8.7 MB]
08黑马文学-分类书籍列表条件查询_.mp4 [27.0 MB]
03黑马文学-分类列表代码实现_.mp4 [37.3 MB]
📁 2_用户登录
13黑马文学-测试用户模拟登录_.mp4 [16.5 MB]
12黑马文学-添加测试用户_.mp4 [8.9 MB]
10黑马文学-请求钩子用户权健校验代码实现_.mp4 [13.0 MB]
05黑马文学-jwt工具封装_.mp4 [17.1 MB]
07黑马文学-用户登录代码实现_.mp4 [35.2 MB]
11黑马文学-登录验证装饰器实现_.mp4 [11.5 MB]
02黑马文学-微信授权流程说明_.mp4 [14.6 MB]
14黑马文学-总结_.mp4 [10.8 MB]
08黑马文学-jwt有效期工具实现_.mp4 [20.6 MB]
01黑马文学-课程介绍_.mp4 [4.1 MB]
04黑马文学-JWT介绍和pyjwt模块_.mp4 [11.3 MB]
03黑马文学-微信平台开发流程_.mp4 [27.8 MB]
09黑马文学-请求钩子用户权限校验步骤说明_.mp4 [5.7 MB]
06黑马文学-用户登录接口分析和步骤_.mp4 [12.8 MB]
📁 5_搜索管理
10黑马文学-搜索精准高匹配推荐代码实现推荐_.mp4 [23.4 MB]
05黑马文学-搜索书本列表代码测试_.mp4 [6.4 MB]
01黑马文学-课程介绍_.mp4 [8.6 MB]
09黑马文学-搜索精准高匹配推荐代码实现精准高匹配_.mp4 [35.9 MB]
02黑马文学-搜索书本列表接口设计_.mp4 [7.1 MB]
03黑马文学-搜索书本列表实现步骤_.mp4 [4.6 MB]
12黑马文学-总结_.mp4 [13.8 MB]
11黑马文学-搜索精准高匹配推荐代码测试_.mp4 [17.3 MB]
08黑马文学-搜索精准高匹配推荐代码实现关键词处理_.mp4 [13.0 MB]
06黑马文学-搜索精准高匹配推荐接口设计_.mp4 [10.4 MB]
07黑马文学-搜索精准高匹配推荐实现步骤_.mp4 [18.0 MB]
04黑马文学-搜索书本列表代码实现_.mp4 [29.0 MB]
📁 7_阅读记录、配置及项目部署
11黑马文学-阅读设置代码实现_.pcwlenv [57.7 MB]
13黑马文学-uWSGI项目部署_.pcwlenv [39.4 MB]
03黑马文学-我的浏览记录实现步骤_.pcwlenv [31.7 MB]
04黑马文学-我的浏览记录代码实现_.pcwlenv [129.8 MB]
15黑马文学-补充flask-restful_.pcwlenv [37.3 MB]
01黑马文学-课程介绍_.pcwlenv [26.2 MB]
05黑马文学-我的浏览记录代码测试_.pcwlenv [39.4 MB]
08黑马文学-阅读偏好代码实现_.pcwlenv [62.8 MB]
14黑马文学-补充异常和日志_.pcwlenv [66.7 MB]
07黑马文学-阅读偏好接口设计和实现步骤_.pcwlenv [40.9 MB]
12黑马文学-阅读设置代码测试_.pcwlenv [28.0 MB]
16黑马文学-总结_.pcwlenv [46.3 MB]
09黑马文学-阅读偏好代码测试_.pcwlenv [45.7 MB]
02黑马文学-我的浏览记录接口设计_.pcwlenv [25.6 MB]
06黑马文学-我的浏览记录清除_.pcwlenv [32.5 MB]
10黑马文学-阅读设置接口设计和实现步骤_.pcwlenv [68.5 MB]
📁 1_项目介绍
12黑马文学-数据库设计书籍&搜索&浏览记录_.mp4 [15.8 MB]
08黑马文学-项目目录数据库&脚本管理器&迁移扩展实现_.mp4 [16.7 MB]
15黑马文学-总结_.mp4 [9.2 MB]
04黑马文学-环境配置说明_.mp4 [5.8 MB]
10黑马文学-项目目录代码拆分_.mp4 [20.7 MB]
01黑马文学-项目介绍_.mp4 [6.4 MB]
03黑马文学-技术架构说明_.mp4 [5.3 MB]
09黑马文学-项目目录工厂函数&蓝图实现_.mp4 [14.4 MB]
07黑马文学-项目目录基本程序实现_.mp4 [12.7 MB]
11黑马文学-数据库设计书架&书籍分类_.mp4 [27.0 MB]
05黑马文学-项目运行方式说明_.mp4 [13.0 MB]
02黑马文学-产品原型说明_.mp4 [12.1 MB]
06黑马文学-项目目录说明_.mp4 [7.1 MB]
13黑马文学-数据库设计书籍卷&章&内容_.mp4 [22.5 MB]
14黑马文学-数据库迁移_.mp4 [20.8 MB]
📁 3_书架管理
02黑马文学-导入书籍_.mp4 [20.5 MB]
13黑马文学-最后阅读代码实现2_.mp4 [24.1 MB]
15黑马文学-总结_.mp4 [3.8 MB]
11黑马文学-最后阅读实现步骤_.mp4 [7.5 MB]
08黑马文学-书架管理添加书籍代码实现_.mp4 [21.8 MB]
12黑马文学-最后阅读代码实现1_.mp4 [39.7 MB]
05黑马文学-书架列表代码实现和测试_.mp4 [17.0 MB]
09黑马文学-书架添加书籍测试_.mp4 [15.0 MB]
07黑马文学-书架管理添加书籍实现步骤_.mp4 [4.8 MB]
03黑马文学-书架列表实现步骤_.mp4 [4.1 MB]
04黑马文学-书架列表代码实现1_.mp4 [34.0 MB]
14黑马文学-最后阅读测试_.mp4 [6.9 MB]
06黑马文学-书架列表补充说明_.mp4 [10.8 MB]
01黑马文学-书籍管理的脚本文件说明_.mp4 [8.6 MB]
10黑马文学-书架删除书籍代码实现和测试_.mp4 [13.2 MB]
📁 6_热门推荐与小说目录
12黑马文学-小说阅读代码实现_.mp4 [26.2 MB]
10黑马文学-小说阅读接口设计_.mp4 [7.3 MB]
09黑马文学-小说目录代码测试_.mp4 [4.9 MB]
16黑马文学-小说详情代码实现补充_.mp4 [5.0 MB]
03黑马文学-同类热门推荐实现步骤_.mp4 [6.0 MB]
05黑马文学-同类热门推荐代码测试_.mp4 [4.4 MB]
08黑马文学-小说目录代码实现_.mp4 [25.4 MB]
18黑马文学-总结_.mp4 [13.0 MB]
13黑马文学-小说阅读代码测试_.mp4 [12.6 MB]
04黑马文学-同类热门推荐代码实现_.mp4 [32.4 MB]
14黑马文学-小说详情实现步骤_.mp4 [6.1 MB]
17黑马文学-小说详情代码测试_.mp4 [5.2 MB]
01黑马文学-课程介绍_.mp4 [3.9 MB]
07黑马文学-小说目录实现步骤_.mp4 [5.2 MB]
15黑马文学-小说详情代码实现_.mp4 [31.6 MB]
02黑马文学-同类热门推荐接口设计_.mp4 [5.0 MB]
11黑马文学-小说阅读实现步骤_.mp4 [3.9 MB]
📁 01阶段_基础班
📁 Day05
📁 预习
📁 视频
📁 资料
📁 笔记
📁 代码
📁 Day05
📁 _idea
Day05.iml [408.0 B]
📁 Day10
📁 笔记
📁 资料
📁 代码
📁 Day10
📁 _idea
Day10.iml [408.0 B]
📁 normal_dir
📁 normal_pack
📁 视频
📁 Day07
📁 预习
📁 视频
📁 笔记
📁 代码
📁 Day07
📁 _idea
Day07.iml [408.0 B]
📁 资料
📁 Day11
📁 资料
📁 视频
📁 笔记
📁 代码
📁 Day11-SMS
📁 _idea
Day11-SMS.iml [398.0 B]
text [2.0 KB]
data [29.0 B]
📁 Day01
📁 视频
📁 资料
📁 代码
📁 Day01
📁 预习
📁 笔记
📁 Day03
📁 笔记
📁 资料
📁 视频
📁 预习
📁 代码
📁 新建文件夹
📁 Day43-03
📁 _idea
Day43-03.iml [398.0 B]
Day43-03(1).iml [398.0 B]
📁 Day43-03
📁 _idea
Day43-03.iml [398.0 B]
Day43-03(1).iml [398.0 B]
📁 Day03
📁 _idea
Day03.iml [398.0 B]
Day03(1).iml [398.0 B]
📁 Day09
📁 视频
📁 预习
📁 笔记
📁 资料
📁 代码
📁 Day09
📁 _idea
Day09.iml [408.0 B]
📁 Day04
📁 预习
📁 资料
📁 视频
📁 笔记
📁 代码
📁 Day04
📁 _idea
Day04.iml [408.0 B]
Day04(1).iml [408.0 B]
📁 Day08
📁 代码
📁 Day08
📁 _idea
Day08.iml [408.0 B]
📁 资料
📁 视频
📁 预习
📁 笔记
📁 Day06
📁 视频
📁 资料
📁 笔记
📁 预习
📁 代码
📁 Day06
📁 _idea
Day06.iml [408.0 B]
📁 Day02
📁 笔记
📁 代码
📁 Day02
📁 _idea
Day02(1).iml [408.0 B]
Day02.iml [408.0 B]
📁 视频
📁 资料
📁 预习
📁 14python加薪课人工智能方向
📁 聚类算法
📁 第二章 算法效果衡量标准
02_00_聚类算法_效果衡量_导入-.mp4 [19.3 MB]
02_08_聚类算法_效果衡量_总结-.mp4 [37.4 MB]
02_03_聚类算法_效果衡量_SC系数-.mp4 [170.0 MB]
02_01_聚类算法_效果衡量_SSE-.mp4 [198.4 MB]
02_07_聚类算法_效果衡量_案例2_图片压缩实战_实践-.mp4 [117.2 MB]
02_06_聚类算法_效果衡量_图片压缩实战-.mp4 [70.0 MB]
02_02_聚类算法_衡量标准_肘部法-.mp4 [99.3 MB]
02_05_聚类算法_衡量标准_优缺点-.mp4 [53.5 MB]
02_04_聚类算法_效果衡量标准_CH系数-.mp4 [218.0 MB]
02_09_聚类算法_效果衡量标准_聚类效果评估_作业-.mp4 [29.0 MB]
📁 第一章 算法原理
01_11_聚类算法_效果衡量_肘部法_实践-.mp4 [38.9 MB]
01_05_聚类算法_算法原理_总结-.mp4 [40.8 MB]
01_02_聚类算法_算法原理_课题导入-.mp4 [88.1 MB]
01_01_聚类算法_内容设置-.mp4 [26.4 MB]
01_03_聚类算法_算法原理_算法解析-.mp4 [156.0 MB]
01_04_聚类算法_算法原理_算法流程-.mp4 [102.3 MB]
01_09_聚类算法_算法原理_工业车辆聚类_预处理实践-.mp4 [124.8 MB]
01_15_聚类算法_算法原理_工业车辆聚类_kmeans算法聚类_实践-.mp4 [135.7 MB]
01_08_聚类算法_算法原理_汽车工业数据聚类前期预处理_实践-.mp4 [97.2 MB]
01_14_聚类算法_算法原理_工业车辆聚类_kmeans算法聚类_实践-.mp4 [208.7 MB]
01_07_聚类算法_算法原理_不同数据集的kmeans聚类_实践-.mp4 [62.0 MB]
01_12_聚类算法_算法原理_工业车辆聚类_特征选择_实践-.mp4 [60.0 MB]
01_06_聚类算法_算法原理_不同数据集的kmeans聚类_案例讲解-.mp4 [66.4 MB]
01_13_聚类算法_算法原理_工业车辆聚类_特征观察_实践-.mp4 [156.9 MB]
01_10_聚类算法_算法原理_工业车辆聚类_特征工程_实践-.mp4 [90.5 MB]
📁 第四章 算法进阶
📁 02_聚类算法_算法进阶_层次聚类_上
04_02_聚类算法_算法进阶_层次聚类_上-.mp4 [49.0 MB]
📁 08_聚类算法_算法进阶_谱聚类
04_06_聚类算法_算法进阶_谱聚类-.mp4 [47.6 MB]
📁 09_聚类算法_算法进阶_小结
04_07_聚类算法_算法进阶_小结.flv [50.7 MB]
📁 11_聚类算法_算法进阶_案例4_kmeans与DBSCAN聚类对比_实践
04_09_聚类算法_算法进阶_案例4_kmeans与DBSCAN聚类对比_实践.flv [179.4 MB]
📁 01_聚类算法_算法进阶_DBSCAN
04_01_聚类算法_算法进阶_DBSCAN-.mp4 [286.5 MB]
📁 07_聚类算法_算法进阶_SOM聚类
04_05_聚类算法_算法进阶_SOM聚类-.mp4 [200.2 MB]
📁 10_聚类算法_算法进阶_Kmeans与DBSCAN聚类比较_案例
04_08_聚类算法_算法进阶_Kmeans与DBSCAN聚类比较_案例.flv [33.0 MB]
📁 06_聚类算法_算法进阶_AP聚类
04_04_聚类算法_算法进阶_AP聚类-.mp4 [194.9 MB]
📁 03_聚类算法_算法进阶_层次聚类_中
04_02_聚类算法_算法进阶_层次聚类_中-.mp4 [25.0 MB]
📁 05_聚类算法_算法进阶_MeanShift聚类
04_03_聚类算法_算法进阶_MeanShift聚类-.mp4 [327.9 MB]
📁 04_聚类算法_算法进阶_层次聚类_下
04_02_聚类算法_算法进阶_层次聚类_下-.mp4 [178.7 MB]
📁 第三章 算法优化
03_04_聚类算法_算法优化_Kernel Kmeans-.mp4 [275.7 MB]
03_02_聚类算法_算法优化_k-means++-.mp4 [53.4 MB]
03_03_聚类算法_算法优化_二分kmeans-.mp4 [54.0 MB]
03_08_聚类算法_算法优化_小结-.mp4 [14.2 MB]
03_01_聚类算法_算法优化_Canopy配合初始聚类-.mp4 [75.1 MB]
03_07_聚类算法_算法优化_MiniBatchKmeans-.mp4 [143.6 MB]
03_06_聚类算法_算法优化_ISODATA-.mp4 [171.8 MB]
03_05_聚类算法_算法优化_K-medoids-.mp4 [184.1 MB]
📁 第五章 综合实践
📁 08_聚类算法_学习提升+资料推荐
05_05_聚类算法_学习提升+资料推荐-.mp4 [82.9 MB]
📁 06_聚类算法_复习
05_03_聚类算法_复习-.mp4 [15.9 MB]
📁 09_聚类算法_综合实践_客户价值分析_作业
05_06_聚类算法_综合实践_客户价值分析_作业-.mp4 [60.7 MB]
📁 03_聚类算法_综合实践_文本文档分析_思路
05_02_聚类算法_综合实践_文本文档分析_思路-.mp4 [38.0 MB]
📁 07_聚类算法_总结与回顾
05_04_聚类算法_总结与回顾-.mp4 [99.0 MB]
📁 05_聚类算法_综合实践_文本文档分析_实践
05_02_聚类算法_综合实践_文本文档分析_实践-.mp4 [191.1 MB]
📁 01_聚类算法_综合实践_客户价值分析_思路
05_01_聚类算法_综合实践_客户价值分析_思路-.mp4 [42.4 MB]
📁 02_聚类算法_算法原理_客户价值分析_实践
05_01_聚类算法_算法原理_客户价值分析_实践-.mp4 [240.5 MB]
📁 04_聚类算法_综合实践_文本文档分析_数据集介绍
05_02_聚类算法_综合实践_文本文档分析_数据集介绍-.mp4 [32.5 MB]
📁 08-图片商品物体检测项目第三阶段
33-.mp4 [17.9 MB]
16-.mp4 [30.2 MB]
34-.mp4 [17.0 MB]
21-.mp4 [15.2 MB]
29-.mp4 [6.7 MB]
02-.mp4 [11.6 MB]
37-.mp4 [16.8 MB]
30-.mp4 [21.0 MB]
04-.mp4 [21.7 MB]
24-.mp4 [58.7 MB]
35-.mp4 [24.0 MB]
07-.mp4 [19.8 MB]
41-.mp4 [23.2 MB]
15-.mp4 [33.3 MB]
08-.mp4 [30.0 MB]
03-.mp4 [15.6 MB]
20-.mp4 [7.5 MB]
13-.mp4 [18.0 MB]
26-.mp4 [30.2 MB]
09-.mp4 [39.3 MB]
06-.mp4 [21.2 MB]
19-.mp4 [46.3 MB]
23-.mp4 [16.0 MB]
22-.mp4 [27.4 MB]
10-.mp4 [26.3 MB]
14-.mp4 [29.0 MB]
12-.mp4 [14.1 MB]
11-.mp4 [14.5 MB]
05-.mp4 [595.3 MB]
25-.mp4 [30.1 MB]
32-.mp4 [52.6 MB]
18-.mp4 [36.4 MB]
01-.mp4 [15.5 MB]
36-.mp4 [43.0 MB]
31-.mp4 [15.8 MB]
27-.mp4 [53.7 MB]
28-.mp4 [44.4 MB]
17-.mp4 [14.8 MB]
39-.mp4 [16.5 MB]
38-.mp4 [16.7 MB]
40-.mp4 [11.8 MB]
📁 09_自然语言处理
53_.mp4 [43.3 MB]
14_.mp4 [15.6 MB]
01_.mp4 [108.4 MB]
63_.mp4 [29.8 MB]
33_.mp4 [34.2 MB]
27_.mp4 [31.1 MB]
11_.mp4 [13.1 MB]
42_.mp4 [11.3 MB]
50_.mp4 [41.1 MB]
48_.mp4 [35.5 MB]
15_.mp4 [10.9 MB]
44_.mp4 [6.6 MB]
64_.mp4 [22.8 MB]
62_.mp4 [25.2 MB]
56_.mp4 [31.2 MB]
36_.mp4 [26.7 MB]
05_.mp4 [40.7 MB]
20_.mp4 [46.9 MB]
17_.mp4 [154.1 MB]
51_.mp4 [24.8 MB]
57_.mp4 [21.0 MB]
34_.mp4 [74.9 MB]
12_.mp4 [33.8 MB]
41_.mp4 [21.3 MB]
59_.mp4 [36.4 MB]
65_.mp4 [15.3 MB]
38_.mp4 [23.6 MB]
67_.mp4 [42.6 MB]
22_.mp4 [38.5 MB]
40_.mp4 [23.8 MB]
23_.mp4 [143.6 MB]
30_.mp4 [123.8 MB]
03_.mp4 [84.1 MB]
60_.mp4 [28.3 MB]
09_.mp4 [7.7 MB]
66_.mp4 [52.4 MB]
26_.mp4 [61.8 MB]
47_.mp4 [41.2 MB]
68_.mp4 [13.2 MB]
69_.mp4 [7.7 MB]
31_.mp4 [17.7 MB]
45_.mp4 [21.0 MB]
04_.mp4 [38.2 MB]
43_.mp4 [19.1 MB]
18_.mp4 [43.6 MB]
02_.mp4 [38.0 MB]
39_.mp4 [30.7 MB]
32_.mp4 [42.1 MB]
07_.mp4 [34.6 MB]
55_.mp4 [62.7 MB]
52_.mp4 [56.4 MB]
25_.mp4 [77.9 MB]
35_.mp4 [12.9 MB]
37_.mp4 [29.4 MB]
19_.mp4 [65.4 MB]
16_.mp4 [78.0 MB]
58_.mp4 [30.6 MB]
46_.mp4 [22.7 MB]
06_.mp4 [46.5 MB]
70_.mp4 [43.9 MB]
24_.mp4 [53.4 MB]
10_.mp4 [7.6 MB]
54_.mp4 [48.9 MB]
13_.mp4 [55.5 MB]
28_.mp4 [66.0 MB]
29_.mp4 [130.6 MB]
49_.mp4 [30.3 MB]
61_.mp4 [30.7 MB]
08_.mp4 [30.7 MB]
21_.mp4 [141.1 MB]
📁 02_深度学习优化进阶
📁 2-2 梯度下降算法优化
03_RMSProp与Adam原理与学习率递减_.mp4 [14.7 MB]
05_作业讲解1_.mp4 [68.3 MB]
04_作业介绍_.mp4 [9.2 MB]
01_Mini梯度下降与Batch梯度下降_.mp4 [29.7 MB]
06_作业讲解2_.mp4 [4.9 MB]
02_指数加权平均_.mp4 [15.5 MB]
📁 2-1 多分类
01_交叉熵损失原理_.mp4 [24.2 MB]
05_调整学习率带来的问题-.mp4 [11.2 MB]
02_案例：Mnist手写数字数据介绍_.mp4 [14.2 MB]
03_案例：主网络结构搭建实现_.mp4 [35.9 MB]
04_案例：添加模型保存、预测_.mp4 [28.5 MB]
📁 2-4 神经网络调参与BN
01_神经网络调参数技巧与如何设置参数、如何运行)_.mp4 [15.8 MB]
02_批标准化定义、公式、为什么有效_.mp4 [50.4 MB]
📁 2-3 深度学习正则化
01_正则化概念、L2正则化与L1正则化_.mp4 [23.0 MB]
02_Droupout过程与原理理解_.mp4 [29.0 MB]
📁 06-图片商品物体检测项目第一阶段
06_.mp4 [13.9 MB]
11_.mp4 [14.5 MB]
29_.mp4 [37.2 MB]
22_.mp4 [15.4 MB]
10_.mp4 [9.2 MB]
24_.mp4 [3.6 MB]
16_.mp4 [16.1 MB]
35_.mp4 [24.0 MB]
05_.mp4 [13.6 MB]
18_.mp4 [9.6 MB]
12_.mp4 [14.1 MB]
27_.mp4 [5.3 MB]
26_.mp4 [23.9 MB]
28_.mp4 [5.9 MB]
21_.mp4 [7.2 MB]
14_.mp4 [8.5 MB]
13_.mp4 [14.5 MB]
33_.mp4 [17.9 MB]
09_.mp4 [21.7 MB]
07_.mp4 [4.0 MB]
15_.mp4 [25.2 MB]
31_.mp4 [3.4 MB]
20_.mp4 [7.5 MB]
34_.mp4 [9.3 MB]
04_.mp4 [9.7 MB]
01_.mp4 [3.2 MB]
23_.mp4 [16.0 MB]
08_.mp4 [30.0 MB]
02_.mp4 [7.3 MB]
17_.mp4 [10.6 MB]
30_.mp4 [4.7 MB]
25_.mp4 [15.7 MB]
19_.mp4 [17.6 MB]
03_.mp4 [6.9 MB]
36_.mp4 [43.0 MB]
32_.mp4 [25.7 MB]
📁 05_人脸识别
5_1_0_人脸打卡案例_介绍-.mp4 [5.8 MB]
3_1_2_语音识别案例_代码浏览-.mp4 [10.8 MB]
2_3_2_通用文字识别_代码-.mp4 [32.3 MB]
3_1_3_语音识别案例_案例-.mp4 [17.3 MB]
5_1_3_案例_获取token-.mp4 [29.5 MB]
5_1_5_案例_主程序1-.mp4 [21.5 MB]
4_1_1_自然语言处理基础技术-.mp4 [25.9 MB]
2_2_2_图像识别_物体检测API_-.mp4 [32.6 MB]
2_3_6_自定义模板_步骤-.mp4 [23.9 MB]
5_1_1_案例_前端部分介绍.vep-.mp4 [15.2 MB]
2_2_8_定制化图像识别_图像分类_(1)-.mp4 [46.1 MB]
2_1_4_人脸检测_获取access_toke-.mp4 [25.3 MB]
2_3_3_通用文字识别_其他版本函-.mp4 [7.0 MB]
2_2_6_定制化图像识别_图像分类_-.mp4 [27.8 MB]
2_3_8_自定义模板_API和代码-.mp4 [17.1 MB]
2_2_3_图像检测识别_菜品识别-.mp4 [24.9 MB]
2_1_9_人脸检测_SDK方式-.mp4 [27.2 MB]
2_2_11_定制化图像识别_物体检测API_错误码-.mp4 [9.3 MB]
2_1_3_人脸检测_步骤和代码浏览-.mp4 [23.8 MB]
2_1_5_人脸检测_调用API(1)-.mp4 [46.2 MB]
2_2_8_定制化图像识别_图像分类_-.mp4 [46.1 MB]
1_3_百度深度学习平台_介绍-.mp4 [22.9 MB]
2_1_2人脸识别_API-.mp4 [35.1 MB]
1_4_百度深度学习平台_创建集群-.mp4 [16.0 MB]
2_1_7_人脸检测_边框-.mp4 [26.3 MB]
2_2_9_定制化图像识别_图像分类-.mp4 [11.9 MB]
2_1_6_人脸检测_图像坐标-.mp4 [16.9 MB]
2_2_1_图像识别功能_应用创建-.mp4 [22.0 MB]
2_1_7_人脸检测_边框(1)-.mp4 [26.3 MB]
1_1_访问入口-.mp4 [12.5 MB]
2_2_4_图像检测_车辆检测-.mp4 [29.3 MB]
2_2_5_定制化图像识别_特点和功-.mp4 [15.9 MB]
2_3_4_车牌识别-.mp4 [15.4 MB]
3_1_1_语音识别_介绍和API-.mp4 [16.7 MB]
2_3_1_功能介绍_创建应用-.mp4 [22.5 MB]
2_3_7_自定义模板_实际创建-.mp4 [19.2 MB]
2_3_10_分类器代码-.mp4 [21.8 MB]
2_3_5_通用票据识别-.mp4 [33.4 MB]
2_1_1_人脸识别功能介绍_开通应用-.mp4 [22.6 MB]
5_1_4_案例_添加用户_人脸搜索-.mp4 [47.7 MB]
2_2_7_定制化图像识别_图像分类_-.mp4 [12.3 MB]
3_2_1语音合成-.mp4 [13.9 MB]
2_3_9_创建分类器-.mp4 [17.3 MB]
1_5_百度人工智能平台_功能介绍-.mp4 [19.7 MB]
2_1_8_人脸检测_性别年龄总结-.mp4 [24.2 MB]
1_6_人工智能平台_服务开通-.mp4 [15.4 MB]
0_课程组成和目标-.mp4 [3.5 MB]
5_1_6_案例_主程序2-.mp4 [41.2 MB]
2_1_5_人脸检测_调用API-.mp4 [46.2 MB]
1_2_机器学习平台_介绍.vep-.mp4 [19.3 MB]
1_7_人工智能平台_访问方式和SD-.mp4 [37.6 MB]
2_2_10_定制化图像识别_物体检测_-.mp4 [21.9 MB]
📁 03_卷积神经网络
📁 3-2 经典分类结构
02_常见网络结构介绍-.mp4 [22.8 MB]
01_LeNet5的计算过程详解-.mp4 [30.0 MB]
📁 3-1 卷积网络原理
06_全连接层-.mp4 [8.8 MB]
05_多通道的卷积与多卷积核-.mp4 [10.4 MB]
04_过滤器大小与步长-.mp4 [18.5 MB]
03_零填充-.mp4 [14.5 MB]
01_卷积网络结构介绍()-.mp4 [11.1 MB]
02_默认卷积的运算过程-.mp4 [9.2 MB]
📁 3-3 CNN实战
01_作业介绍-.mp4 [8.0 MB]
02_迁移学习-.mp4 [26.6 MB]
📁 07-图片商品物体检测项目第二阶段
09_.mp4 [30.9 MB]
11_.mp4 [10.6 MB]
08_.mp4 [26.8 MB]
01_.mp4 [18.5 MB]
02_.mp4 [27.1 MB]
05_.mp4 [36.3 MB]
06_.mp4 [80.1 MB]
04_.mp4 [28.2 MB]
03_.mp4 [10.4 MB]
10_.mp4 [15.6 MB]
07_.mp4 [72.4 MB]
📁 04_循环神经网络
📁 4-1 循环神经网络
03_词的表示与矩阵形状运算-.mp4 [25.8 MB]
06_手写RNN案例：所有cell的前向传播-.mp4 [26.3 MB]
02_循环神经网络结构原理-.mp4 [21.4 MB]
04_梯度消失、案例介绍-.mp4 [14.9 MB]
01_循环神经网络背景介绍-.mp4 [11.2 MB]
05_手写RNN案例：单个cell前向传播-.mp4 [19.3 MB]
📁 4-3 seq2seq与Attention机制
05_机器翻译案例：训练逻辑与网络结构介绍-.mp4 [17.9 MB]
01_seq2seq介绍与理解-.mp4 [18.8 MB]
04_机器翻译案例：数据获取以及数据格式转换介绍-.mp4 [14.8 MB]
08_机器翻译案例：model中计算attention输出c逻辑函数实现-.mp4 [20.5 MB]
03_机器翻译案例：模型参数定义-.mp4 [14.6 MB]
06_机器翻译案例：自定义网络seq2seq的编解码器定义-.mp4 [28.5 MB]
02_机器翻译案例：日期格式翻译转换、代码结构介绍-.mp4 [16.0 MB]
07_机器翻译案例：seq2seq的输出层定义-.mp4 [8.4 MB]
📁 4-2 词嵌入
02_词嵌入案例-.mp4 [27.2 MB]
01_词嵌入介绍-.mp4 [17.8 MB]
📁 01_深度学习基础
📁 1-1 深度学习介绍
02_深度学习介绍-.mp4 [26.6 MB]
01_深度学习课程介绍-.mp4 [6.4 MB]
📁 1-3 浅层神经网络
07_作业实现：网络模型逻辑实现-.mp4 [16.2 MB]
06_作业实现：反向传播与更新梯度-.mp4 [27.5 MB]
02_浅层神经网络的前向传播-.mp4 [11.1 MB]
03_浅层神经网络的反向传播-.mp4 [17.4 MB]
08_总结-.mp4 [6.8 MB]
05_作业实现：初始化模型与前向传播-.mp4 [24.0 MB]
01_浅层神经网络表示-.mp4 [13.2 MB]
04_作业介绍-.mp4 [6.4 MB]
📁 1-4 深层神经网络
02_深层神经网络的反向传播过程-.mp4 [9.3 MB]
01_深层神经网络表示-.mp4 [13.9 MB]
📁 1-2 神经网络基础
01_逻辑回归介绍-.mp4 [25.2 MB]
09_总结-.mp4 [13.0 MB]
07_作业讲解题1：实现sigmoid函数与梯度实现-.mp4 [5.9 MB]
02_逻辑回归损失函数-.mp4 [13.6 MB]
05_导数计算图与链式法则-.mp4 [23.2 MB]
03_梯度下降算法过程以及公式-.mp4 [16.9 MB]
08_作业讲解题2：单神经元神经网络(logistic)分类作业流程介绍-.mp4 [8.7 MB]
04_导数意义介绍-.mp4 [7.4 MB]
06_逻辑回归的导数计算图分析以及参数导数-.mp4 [18.4 MB]
📁 4_1_高级主题
12.01_CapsuleNet了解(Av98007795,P12)-.mp4 [25.5 MB]
3.05_生成数字图片案例：训练流程(Av98007795,P3)-.mp4 [33.4 MB]
2.04_生成数字图片案例：模型初始化代码编写(Av98007795,P2)-.mp4 [39.6 MB]
10.06_案例：降噪编码器介绍(Av98007795,P10)-.mp4 [7.9 MB]
1.01_高级主题介绍、GAN介绍(Av98007795,P1)-.mp4 [24.7 MB]
4.06_生成数字图片案例：运行保存图片并对比(Av98007795,P4)-.mp4 [11.5 MB]
6.02_案例：编码器类别、普通自编码器流程、模型初始化逻辑(Av98007795,P6)-.mp4 [29.7 MB]
11.07_案例：降噪编码器案例(Av98007795,P11)-.mp4 [13.6 MB]
13.02_深度学习课程总结(Av98007795,P13)-.mp4 [21.7 MB]
5.01_自动编码器介绍(Av98007795,P5)-.mp4 [8.7 MB]
8.04_案例：深度自编码器编写演示(Av98007795,P8)-.mp4 [7.3 MB]
9.05_案例：卷积自编码器编写演示(Av98007795,P9)-.mp4 [14.1 MB]
7.03_案例：训练普通自编码器(Av98007795,P7)-.mp4 [25.0 MB]
📁 03阶段-Django视频
📁 06-Django项目基础-第06天-框架+Git
📁 05-Django项目基础-第05天-框架 --加密
📁 02-Django项目基础-第02天-框架
📁 01-Django项目基础-第01天-Redis
📁 03-Django项目基础-第03天-框架
📁 04-Django项目基础-第04天-框架
📁 08-Django项目基础-第08天-Vue
📁 07-Django项目基础-第07天-Git
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