尚硅谷人工智能大模型
课程详情
课程详情
几米课堂自成立以来，始终聚焦前沿技术教育领域，以 “让每一位学习者都能掌握实用技术” 为使命，累计服务超过 10 万名学员，其中 85% 的学员成功实现职业转型或技能升级。
核心课程：尚硅谷人工智能大模型 —— 从入门到精通的系统化方案
当前大模型学习存在三大难题：基础薄弱、实战技巧不足、缺乏项目经验。这门课恰好针对性解决这些问题，通过动画演示、类比案例、真实业务场景讲解，以及从个人小项目到企业级部署的完整项目链，让你学到真正符合行业需求的核心技能。
详细学习阶段：5 大模块，循序渐进构建大模型知识体系
- 阶段 1：大模型基础入门（40 小时）
- 阶段 2：大模型底层原理精讲（60 小时）
- 阶段 3：大模型训练与微调实战（70 小时）
- 阶段 4：多模态大模型与企业级部署（60 小时）
- 阶段 5：项目实战与就业冲刺（60 小时）
适合人群
- 零基础转型者
- 技术提升者
- 企业技术负责人
- 创业者与爱好者
课程特色：6 大优势，让你的学习事半功倍
- 顶尖师资团队
- 极致学习体验
- 海量学习资源
- 实战保障
- 后续服务
- 企业合作优势
课程目录
00_【大模型理论和开发】
1《大模型原理&基础》
0-预备知识：Transformer
Attention Is All You Need.pdf
源代码+教程（只打开里面的html文件即可）
代码+讲解.html
代码+讲解_files
vega-embed@6
vega-lite@4.8.1
vega@5
理论+编程 视频讲解
0 Transformer理论讲解.mp4
1 深入剖析PyTorch中的Transformer API源码.mp4
2 Transformer模型Encoder原理精讲及其PyTorch逐行实现.mp4
3 Transformer Decoder原理精讲及其PyTorch逐行实现.mp4
4 Transformer Masked loss原理精讲及其PyTorch逐行实现.mp4
英文原版讲解推荐.txt
1-GPT 1-4 讲解
GPT1-3讲解.mp4
GPT4 GPTs are GPTs- An Early Look at the Labor Market Impact Potential of Large Language Models.pdf
GPT4 Toolformer- Language Models Can Teach Themselves to Use Tools.pdf
GPT-4.mp4
gpt1.pdf
gpt2.pdf
gpt3.pdf
2-Llama 3.1 讲解
1-导读.mp4
2-预训练数据.mp4
3-模型结构.mp4
The Llama 3 Herd of Models.pdf
3-相关论文推荐
A Comparative Study on ChatGPT and Fine-tuned BERT.pdf
A Survey on ChatGPT and Beyond.pdf
A Survey on Evaluation of Large Language Models .pdf
A Systematic Study and Comprehensive Evaluation of ChatGPT on Benchmark Datasets.pdf
An Independent Evaluation of ChatGPT on Mathematical Word Problems (MWP) .pdf
BERT Rediscovers the Classical NLP Pipeline.pdf
ChatGPT- A Meta-Analysis after 2.5 Months.pdf
ChatLog- Recording and Analyzing ChatGPT Across Time.pdf
GPT Understands, Too.pdf
GPT-3- Its Nature, Scope, Limits, and Consequences.pdf
How Contextual are Contextualized Word Representations.pdf
Is ChatGPT A Good Translator.pdf
Sparks of Artificial General Intelligence.pdf
Summary of ChatGPT GPT-4 Research .pdf
What Makes Good In-Context Examples for GPT-3.pdf
gpt3_whats_it_good_for.pdf
4-LLM&GPT的复现和实践
GPT2-pytorch.zip
GPT2-tensorflow复现.zip
GPT2-中文版 结合bert分词.zip1(请把后缀改成zip再解压)
gpt2+3 tensorflow版.zip
gpt2-Pytorch版.zip
minGPT-pytorch.zip
prompt——gpt提示工程指南.zip
★ DialoGPT-微软开源对话gpt项目.zip
★ gpt2的训练-中文.zip
中文GPT2新闻标题生成项目.zip
中文闲聊的GPT2模型.zip
基于GPT2的闲聊模型-中文.zip
2《大模型实践、应用、开发》
0-大模型系列课程
1-【吴恩达大模型课程】
01.课程介绍.mp4
02.Prompt 的构建原则.mp4
03.Prompt如何迭代优化.mp4
04.总结摘要.mp4
05.AI推理.mp4
06.AI转译.mp4
07.AI文案生成.mp4
08.聊天机器人.mp4
09.课程完结.mp4
配套代码和教程.zip
此处机构课程因容量太大，放外链.txt
1-主流开源大模型
InternLM系列
InternLM
01-InternLM-Chat-7B Transformers 部署调用.md
02-internLM-Chat-7B FastApi.md
03-InternLM-Chat-7B.md
04-Lagent+InternLM-Chat-7B-V1.1.md
05-浦语灵笔图文理解&创作.md
06-InternLM接入LangChain搭建知识库助手
LLM.py
creat_db.py
readme.md
run_gradio.py
06-InternLM接入LangChain搭建知识库助手.md
images
image-1.png
image-2.png
image-3.png
image-4.png
image-5.png
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image-14.png
image.png
InternLM2
01-InternLM2-7B-chat FastAPI部署.md
02-InternLM2-7B-chat langchain 接入.md
03-InternLM2-7B-chat WebDemo 部署.md
04-InternLM2-7B-chat Xtuner Qlora 微调.md
dataset
心理大模型-职场焦虑语料.xlsx
images
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4-1.png
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4-4.png
InternLM-main.zip
LCM-LORA-让实时文字生成图像速度提升5-10倍（清华出品）
latent-consistency-model-main.zip
中文介绍.pdf
论文.pdf
Mistral-混合专家模型
client-python-main.zip
中文介绍.pdf
开发操作讲解.mp4
YUAN-最新千亿大模型免费商用 1026亿参数 无需授权
Yuan-1.0-main.zip
Yuan-2.0-main.zip
中文介绍.pdf
论文.pdf
★ ★ ★ ChatGLM系列模型
ChatGLM1
ChatGLM-6B-main.zip
ChatGLM2
ChatGLM2-6B 理论、部署和微调.mp4
ChatGLM2-6B-main.zip
ChatGLM3
ChatGLM3-6B 理论、部署和微调（官方）.mp4
ChatGLM3-main.zip
chatglm3-6b开发分享ppt.pdf
教程
01-ChatGLM3-6B Transformer部署调用.md
02-ChatGLM3-6B FastApi部署调用.md
03-ChatGLM3-6B-chat.md
04-ChatGLM3-6B-Code-Interpreter.md
05-ChatGLM3-6B接入LangChain搭建知识库助手
LLM.py
create_db.py
run_gradio.py
05-ChatGLM3-6B接入LangChain搭建知识库助手.md
06-ChatGLM3-6B-Lora微调.ipynb
06-ChatGLM3-6B-Lora微调.md
06-ChatGLM3-6B-Lora微调.py
images
image-1.png
image-2.png
image-3.png
image-4.png
image-5.png
image-6.png
image-7.png
image-8.png
image-9.png
ChatGLM4
ChatGLM4 教程
01-GLM-4-9B-chat FastApi 部署调用.md
02-GLM-4-9B-chat langchain 接入.md
03-GLM-4-9B-Chat WebDemo.md
04-GLM-4-9B-Chat vLLM 部署调用.md
05-GLM-4-9B-chat Lora 微调.ipynb
05-GLM-4-9B-chat Lora 微调.md
benchmark_throughput.py
images
image01-1.png
image01-2.png
image01-3.png
image01-4.png
image01-5.png
image02-1.png
image03-1.png
image03-2.png
image04-1.png
image-1.png
ChatGLM-6B-main.zip
相关项目
基于 PEFT 的高效 ChatGLM 微调
ChatGLM-Efficient-Tuning-main.zip
基于LLaMA-Factory的ChatGLM3模型微调
LLaMA-Factory-main.zip
视频讲解.mp4
基于LoRA的ChatGLM-6B微调
ChatGLM-Tuning-master.zip
★ ★ ★ LLaMa
LLaMA3 教程
01-LLaMA3-8B-Instruct FastApi 部署调用.md
02-LLaMA3-8B-Instruct langchain 接入.md
03-LLaMA3-8B-Instruct WebDemo 部署.md
04-LLaMA3-8B-Instruct Lora 微调.md
LLaMA3-8B-Instruct Lora.ipynb
images
api_resp.png
api_start.png
image-1.png
image-2.png
image-3.png
LLaMa-1 技术详解.pdf
Llama 2（从原理到实战）.pdf
Llama 3.1 开源系列
Llama-中文教程.zip
llama3-main.zip
llama3-中文教程（偏基础）.zip
中文介绍.pdf
Llama 3.2 -支持图像推理 还有可在手机上运行的版本.pdf
llama-main.zip
llama-recipes-main.zip
★ ★ ★ 阿里-通义千问系列模型
Qwen1.5 教程
01-Qwen1.5-7B-Chat FastApi 部署调用.md
02-Qwen1.5-7B-Chat 接入langchain搭建知识库助手.md
03-Qwen1.5-7B-Chat WebDemo.md
04-Qwen1.5-7B-chat Lora 微调.md
05-Qwen1.5-7B-Chat-GPTQ-Int4 WebDemo.md
06-Qwen1.5-MoE-A2.7B.md
07-Qwen1.5-7B-Chat vLLM 推理部署调用.md
08-Qwen1.5-7B-chat LoRA微调接入实验管理.ipynb
08-Qwen1.5-7B-chat LoRA微调接入实验管理.md
Qwen1.5-7B-Chat Lora.ipynb
benchmark_throughput.py
images
2.png
6.png
Qwen1.5-7b-gptq-int4-1.png
Qwen1.5-7b-gptq-int4-2.png
Qwen1.5-vllm-api-stat.png
Qwen1.5-vllm-gpu-select.png
Qwen1.5-vllm.png
Qwen2-Web1.png
Qwen2-Web2.png
image-2.png
question_to_the_Qwen2.png
swanlabcallbacks.png
swanlabchart.png
swanlabdisplay.png
swanlabsettings.png
swanlabweb.png
Qwen2
Qwen2-main.zip
中文介绍.pdf
Qwen 教程
01-Qwen-7B-Chat Transformers部署调用.md
02-Qwen-7B-Chat FastApi 部署调用.md
03-Qwen-7B-Chat WebDemo.md
04-Qwen-7B-Chat Lora 微调.ipynb
04-Qwen-7B-Chat Lora 微调.md
04-Qwen-7B-Chat Lora 微调.py
05-Qwen-7B-Chat Ptuning 微调.md
05-Qwen-7B-Chat Ptuning 微调.py
06-Qwen-7B-chat 全量微调.md
07-Qwen-7B-Chat 接入langchain搭建知识库助手
LLM.py
creat_db.py
readme.md
run_gradio.py
07-Qwen-7B-Chat 接入langchain搭建知识库助手.md
08-Qwen-7B-Chat Lora -4bit微调.ipynb
08-Qwen-7B-Chat Lora -8bit微调.ipynb
08-Qwen-7B-Chat Lora 低精度微调.md
08-Qwen-7B-Chat Lora 低精度微调.py
09-Qwen-1_8B-chat CPU 部署 .ipynb
09-Qwen-1_8B-chat CPU 部署 .md
environment.yml
images
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2.png
3.png
4.png
5.png
6.png
7.png
8.png
P-tuning.png
Qwen-Agent-main.zip
Qwen-Audio 教程
01-Qwen-Audio-chat FastApi.md
02-Qwen-Audio-chat WebDemo.md
images
image-1.png
image-2.png
image-3.png
image-4.png
Qwen-VL-master.zip
Qwen-main.zip
中文介绍.pdf
相关项目
阿里云开发大模型-实现天气预报
1-零基础微调实战.mp4
2-大模型SFT微调之生成JSON数据集.mp4
视频涉及代码
解压后使用.zip
★ 低成本配置下部署LLaMA-2模型ColossalAI-main.zip
★ 难度大 集成了几乎所有主流大模型OpenLLM-main.zip
【图文大模型】
Bunny-3B-多模态小模型新 SOTA 性能媲美 LLaVA-13B
Bunny-main.zip
中文介绍.pdf
DreamLLM-协同的多模态理解和创造大模型
2309.11499.pdf
DreamLLM-master.zip
介绍.pdf
MoE-LLaVA-将多模态大模型稀疏化
MoE-LLaVA-main.zip
中文介绍.pdf
论文.pdf
Video-LLaVA视觉语言大模型（北大出品）
Video-LLaVA-main.zip
中文介绍.pdf
论文.pdf
miniGPT
MINIGPT-4.pdf
MINIGPT-5.pdf
MiniGPT-5 多模态大模型 GPT5精简版 难度较大.zip
miniGPT-4介绍 论文讲解.mp4
写小说大模型 ChatRWKV-main.zip
图文大模型 Chinese-LLaVA-main
2304.08485.pdf
介绍.pdf
图文大模型 Chinese-LLaVA-main.zip
图文大模型 Visual-Chinese-LLaMA-Alpaca-main.zip
图文大模型 VisCPM.zip2（去掉后缀2再解压）
百川多模态大模型 教程
01-Baichuan2-7B-chat+FastApi+部署调用.md
02-Baichuan-7B-chat+WebDemo.md
03-Baichuan2-7B-chat接入LangChain框架.md
04-Baichuan2-7B-chat Lora 微调.ipynb
04-Baichuan2-7B-chat+lora+微调.md
images
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综合能力强 CogVLM
CogVLM-main.zip
cogvlm-paper.pdf
介绍.pdf
腾讯-中文原生混元文生图大模型
HunyuanDiT-main.zip
中文介绍.pdf
论文.pdf
视觉-文字 LLaVA-main
2310.03744.pdf
介绍.pdf
视觉-文字 LLaVA-main.zip
语音 图像 文字 大模型LLaSM-main.zip
【特殊应用领域的大模型】
GraphGPT-通用图大模型
GraphGPT-main.zip
中文介绍.pdf
论文.pdf
MathGLM-2B-算数能力比GPT4好的数学模型
MathGLM-main.zip
中文介绍.pdf
论文.pdf
MeshGPT-Transformer变革3D建模大模型
meshgpt-pytorch-main.zip
中文介绍.pdf
论文.pdf
SOTA数学推理模型.zip
中文智慧法律问答大模型DISC-LawLLM.zip
全球首个开源多模态医疗基础模型-人工打分平均超越GPT-4V 支持2D_3D放射影像
RadFM-main.zip
中文介绍.pdf
论文.pdf
北大aiXcoder-最强代码大模型
aiXcoder-7B-main.zip
医学诊断大模型 XrayPULSE-main.zip
大模型&自动驾驶 项目未开源
介绍.pdf
论文.pdf
大模型与医疗结合
Data-Centric-FM-Healthcare-master.zip
中文介绍.pdf
论文.pdf
大模型驱动的AI游戏 复杂难度大 ChatDev-main.zip
谷歌Med-Gemini-医学大模型
中文介绍.pdf
论文.pdf
【视频大模型】
StreamingT2V-从文本生成一致的、动态的、可扩展的长视频
StreamingT2V-main.zip
中文介绍.pdf
论文.pdf
北大Open Sora- 已支持国产AI芯片
Open-Sora-Plan-main.zip
文字-视频 大模型Valley-main.zip
教程-通过降低模型精度 加速模型训练 降低部署成本 但是有点麻烦不是很推荐.ipynb
最多400万token上下文 推理提速22倍streaming-llm-main.zip
目前最大的开源模型 34B参数量 Aquila2
Aquila2-main.zip
介绍.pdf
2-微调 fine-tune
1-理论讲解视频
P01 Introduction.mp4
P02 Why FineTune.mp4
P03 Where finetuning fits in.mp4
P04 Instruction Finetuning.mp4
P05 Data Preparationra.mp4
P06 Training Process.mp4
P07 Evaluation and Iteration.mp4
P08 ConsiderationOnGettingStart.mp4
P09 Conclusion.mp4
视频配套代码
01_Why_finetuning_lab_student.ipynb
02_Where_finetuning_fits_in_lab_student.ipynb
03_Instruction_tuning_lab_student.ipynb
04_Data_preparation_lab_student.ipynb
05_Training_lab_student.ipynb
06_Evaluation_lab_student.ipynb
lamini_docs.jsonl
lm-evaluation-harness.zip
utilities.py
2-练手项目&论文
DoRA-一种新的参数高效微调方法
DoRA-main.zip
中文介绍.pdf
论文.pdf
Finetune_LLMs-main.zip
Generate and enrich datasets on-demand to fine-tune LLMs.zip
LoRA and LLaMA-Adapter fine-tuning.zip
LoRA微调 比较基础.zip
a framework and no-code GUI for fine-tuning LLMs..zip
★ LLaMA模型高效微调 Efficient-Tuning-main.zip
★ SOTA级微调方法综述 我找不到比他更全面的资料了.zip
★★★斯坦福-llama 模型开发（微调）.zip
★复现、比较好几种微调方法 LLM-Adapters-main.zip
低成本微调Run large language models at home_ BitTorrent-style.zip
999-【机构课程】
AI大模型微调实战训练营
1：大模型综述[微信 itcodeba]【海量课 todo1024.com】.mp4
2：大数据和大模型，常见分词方法[微信 itcodeba]【海量课 todo1024.com】.mp4
3：项目实战：文旅对话大模型实战（模型参数微调）[微信 itcodeba]【海量课 todo1024.com】.mp4
4：项目实战：文旅对话大模型实战（prefixtuning和adapter）[微信 itcodeba]【海量课 todo1024.com】.mp4
5：项目实战；知识库Langchain项目实战（lora和langchain）[微信 itcodeba]【海量课 todo1024.com】.mp4
6：模型并行[微信 itcodeba]【海量课 todo1024.com】.mp4
7：GPU的计算原理[微信 itcodeba]【海量课 todo1024.com】.mp4
8：大模型技术一览，一些细节[微信 itcodeba]【海量课 todo1024.com】.mp4
9：大模型面试题[微信 itcodeba]【海量课 todo1024.com】.mp4
10：项目实战RAG[微信 itcodeba]【海量课 todo1024.com】.mp4
11：模型解码优化[微信 itcodeba]【海量课 todo1024.com】.mp4
12：项目实战：大模型写作，nl2sql[微信 itcodeba]【海量课 todo1024.com】.mp4
13：角色扮演Agent[微信 itcodeba]【海量课 todo1024.com】.mp4
14：距离精讲[微信 itcodeba]【海量课 todo1024.com】.mp4
15：向量数据库基础[微信 itcodeba]【海量课 todo1024.com】.mp4
预习资料：Attention模型[微信 itcodeba]【海量课 todo1024.com】.mp4
预习资料：Transformer和bert[微信 itcodeba]【海量课 todo1024.com】.mp4
tx-大模型微调实战营-应用篇
01 第一周
01 第一节 年1月21日
01 开营+大模型介绍、Transformer
01 开营【微信 itcodeba 】【资源站 www.todo1024.com】.mp4
02 大模型爆发式发展【微信 itcodeba 】【资源站 www.todo1024.com】.mp4
03 大模型是如何炼成的【微信 itcodeba 】【资源站 www.todo1024.com】.mp4
04 Transformer的应用【微信 itcodeba 】【资源站 www.todo1024.com】.mp4
05 Self-Attention【微信 itcodeba 】【资源站 www.todo1024.com】.mp4
02 第二周
01 第二节 年1月28日
01 Transformer、Encoder、Advanced
01 Transformer Part1【微信 itcodeba 】【资源站 www.todo1024.com】.mp4
02 Transformer Part2【微信 itcodeba 】【资源站 www.todo1024.com】.mp4
03 Encoder-based and Decoder Based LLMs【微信 itcodeba 】【资源站 www.todo1024.com】.mp4
04 Advanced Topics【微信 itcodeba 】【资源站 www.todo1024.com】.mp4
03 第三周
01 第三节 年2月25日
01 大模型微调概览 Lora微调
01 大模型微调概览【微信 itcodeba 】【资源站 www.todo1024.com】.mp4
02 Lora微调-Lora算法【微信 itcodeba 】【资源站 www.todo1024.com】.mp4
03 Lora微调-从零实现Lora到Roberta【微信 itcodeba 】【资源站 www.todo1024.com】.mp4
04 第四周
01 第四节 年3月3日
01 Alpaca、AdaLoRA、QLoRA
01 Alpaca【微信 itcodeba 】【资源站 www.todo1024.com】.mp4
02 AdaLoRA【微信 itcodeba 】【资源站 www.todo1024.com】.mp4
03 QLoRA【微信 itcodeba 】【资源站 www.todo1024.com】.mp4
05 第五周
01 第五节 年3月17日
01 Prefix Tuning、Quantization
01 Prefix Tuning【微信 itcodeba 】【资源站 www.todo1024.com】.mp4
02 Quantization01【微信 itcodeba 】【资源站 www.todo1024.com】.mp4
03 Quantization02【微信 itcodeba 】【资源站 www.todo1024.com】.mp4
04 Quantization Methos for LLM【微信 itcodeba 】【资源站 www.todo1024.com】.mp4
资料（参考）
课件
第一节-拓展资料 0121【微信 itcodeba 】【资源站 www.todo1024.com】.txt
课程资料
第三节-课程资料 0225
Lora代码【微信 itcodeba 】【资源站 www.todo1024.com】.ipynb
课程相关资料【微信 itcodeba 】【资源站 www.todo1024.com】.text
第四节-课程资料 0303
4bit-normalquantization【微信 itcodeba 】【资源站 www.todo1024.com】.ipynb
3-Langchain
1-理论讲解视频
1_LangChain_Intro_v02.zh_gpt_subtitl….mp4
2_LangChain_L1_v02.zh_gpt_subtitled.mp4
3_LangChain_L2_v02.zh_gpt_subtitled.mp4
4_LangChain_L3_v02.zh_gpt_subtitled.mp4
5_LangChain_L4_v02.zh_gpt_subtitled.mp4
6_LangChain_L5_v02.zh_gpt_subtitled.mp4
7_LangChain_L6_v03.zh_gpt_subtitled.mp4
8_LangChain_Conclusion_v02.zh_gpt_su….mp4
【官方教程】ChatGLM + LangChain ….mp4
2-练手项目&论文
GPT4结合langchain处理pdf.zip
LangChain教程 可惜是英文.zip
Langchain 难度很大 涉及java 前后端开发等.zip
★ LangChain 中文入门教程.zip
★ 基于LangChain和ChatGLM-6B等的本地知识库的自动问答.zip
★★ 推荐 Langchain结合ChatGLM.zip
一个简单的LangChain复现
一个简单的例子.mp4
一个简单的中文版教程-ChatGLM实战 基于LangChain构建自己的私有知识库.pdf
中文langchain项目-小必应 蛮有意思的.zip
现有Langchain索引大全 awesome-langchain-main.zip
难度大 应用级开发 langchain-master.zip
难度大 需要openAI账号 Building Apps with LLMs.zip
难度很大 慎做 Langchain apps in production using Jina and FastAPI.zip
（推荐）Chatchat-本地知识库开源项目 搭建详解
1-整体介绍.mp4
2-项目讲解.mp4
3-项目总结&注意事项.mp4
Langchain-Chatchat-master.zip
4-Agent
1-理论讲解视频
1-Agent简介.mp4
2-Agent具体组成.mp4
3-Agent智能体的规划与提示词的关系.mp4
4-Agent应用原理剖析：AutoGPT、HuggingFPT等.mp4
5-Agent应用原理剖析：AutoGPT、HuggingFPT等.mp4
999-最后再看这个视频梳理一遍.mp4
课件
01Introduction.pptx
02Component.pptx
03Planning.pptx
04Application.pptx
05Summary.pptx
2-Agent文字教程
1-Agent的颠覆性影响.pdf
2-Agents 组件详解.pdf
3-AutoGPT.pdf
4-AgentGPT.pdf
5-HuggingGPT.pdf
6-MetaGPT.pdf
7-AI-town 虚拟小镇.pdf
8-API-Bank & AgentBench.pdf
9-思考 Agent.pdf
大语言模型智能体(LLM Agents)入门指南.pdf
3-练手项目&论文
Agent评估项目（平台） AgentBench-main.zip
An LLM-powered autonomous agent platform.zip
AutoChain-构建轻量级、可扩展和可测试的LLM代理AutoChain-main.zip
OpenAgents- AN OPEN PLATFORM FOR LANGUAGE AGENTS IN THE WILD
OpenAgents- AN OPEN PLATFORM FOR LANGUAGE AGENTS IN THE WILD.pdf
OpenAgents-main.zip
Webarena-用于构建自主代理的现实web环境
Webarena-用于构建自主代理的现实web环境.pdf
webarena-main.zip
中文-推荐 Bisheng开源项目 bisheng-main.zip
仅限OpenAI-The open-source hub to build & deploy GPT LLM Agents botpress-master.zip
利用多个 Agent 任务交互轨迹对 LLM 进行指令调整的方法 AgentTuning-main.zip
在浏览器中组装、配置和部署自主AI Agents.zip
应用程序中部署多个基于llm的代理 AgentVerse-main.zip
推荐 An Open-source Framework for Autonomous Language Agents
Agents- An Open-source Framework for Autonomous Language Agents.pdf
agents-master.zip
推荐 一个跟标准的Agent项目 XAgent-main.zip
清华出品-结合《我的世界》开发Agent
GITM-main.zip
基于文本的知识和记忆的大型语言模型为开放世界环境提供一般能力的代理.pdf
自定义LLM代理的无代码平台.zip
英伟达出品-具有LLM的开放式Agent（结合我的世界游戏）
Voyager-main.zip
论文原文.pdf
论文
Agent综述.pdf
Agent论文、项目大全（索引）.pdf
999-【机构课程1】
第1章 多模型强应用：AI2.0时代应用开发者机会
1-1 深入了解课程，让你少走弯路，必看！！！【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
1-2 带你快速了解大语言模型(LLM)基础与发展【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
1-3 国内外主要LLM及特点介绍【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
1-4 大模型的不足以及主要解决方案【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
1-5 AIGC产业拆解以及常见名词解释【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
1-6 应用级开发者如何拥抱AI2.0时代？【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
1-7 智能体(agent)命理大师虚拟项目（需求分析、技术选型、技术分解）【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
第2章 初识langchain：LLM大模型与AI应用的粘合剂
2-1 初始langchain：LLM大模型与AI应用的粘合剂【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
2-2 langchain是什么以及发展过程【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
2-3 langchain能做什么和能力一览【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
2-4 langchain的优势与劣势分析【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
2-5 langchain使用环境的搭建【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
2-6 先跑起来：第一个实例，了解langchain的基本模块【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
2-7 本章梳理与总结【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
第3章 LangChain核心模块与实战：用prompts模板控制LLM的输入输出
3-1 章节介绍【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
3-2 模型IO 大语言模型的交互接口【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
3-3 prompts模板：更加高级和灵活的提示词工程【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
3-4 prompts实战两种主要的提示词模板【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
3-5 自定义prompts模板【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
3-6 两种模板引擎以及组合模板使用【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
3-7 序列化模板使用【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
3-8 示例选择器之根据长度动态选择提示词示例组【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
3-9 示例选择器之MMR与最大余弦相似度【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
3-10 langchain核心组件：LLMs vs chat models【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
3-11 更好的体验：流式输出【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
3-12 花销控制：token消耗追踪【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
3-13 输出结构性：不止于聊天【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
3-14 本章小结【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
第4章 LangChain知识库构建与RAG设计：增强自己大模型能力，实现与各种文档对话
4-1 本章介绍【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
4-2 RAG：检索增强生成是什么？【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
4-3 loader：让大模型具备实时学习的能力【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
4-4 文档转换实战：文档切割【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
4-5 文档转换实战：总结精炼和翻译【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
4-6 Lost in the middle 长上下文精度处理问题【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
4-7 文本向量化实现方式【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
4-8 与AI共舞的向量数据库【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
4-9 Chatdoc 又一个智能文档助手（1）【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
4-10 Chatdoc 又一个智能文档助手（2）【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
4-11 ChatDoc 几种检索优化的方式【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
4-12 ChatDoc 与文件聊天交互【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
4-13 本章小结【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
第5章 LangChain链与记忆处理：带你实现大模型记忆增强，让你的大模型更加智能
5-1 本章介绍【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
5-2 chains：langchain的重要组成部件【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
5-3 四种基本的内置链的介绍与使用(1)【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
5-4 四种基本的内置链的介绍与使用(2)【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
5-5 四种基本的内置链的介绍与使用(3)【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
5-6 四种基本的内置链的介绍与使用(4)【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
5-7 四种基本的内置链的介绍与使用(5)【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
5-8 链的不同调用方法和自定义【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
5-9 四种处理文档的预制链(1)【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
5-10 四种处理文档的预制链(2)【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
5-11 四种文档预制链使用(3)【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
5-12 四种文档预制链使用(4)【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
5-13 memory工具使用(1)【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
5-14 Memory工具使用(2)【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
5-15 Memory工具使用(3)【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
5-16 为链增加memory（1）【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
5-17 为链增加memory(2)【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
5-18 主要的预制链和memory工具【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
5-19 本章小结【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
第6章 Agent核心与实践：初窥未来机器人，学Agent基本开发，让大模型不止于聊天
6-1 本章介绍【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
6-2 什么是agent【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
6-3 第一个agent【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
6-4 几种主要的agents类型介绍（1）【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
6-5 几种主要的agents类型介绍（2）【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
6-6 agent中正确添加memory的方式【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
6-7 如何让agent与tool共享记忆【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
6-8 tool的使用【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
6-9 tookit的使用【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
6-10 LCEL是什么【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
6-11 LCEL不同的接口实现【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
6-12 LCEL里chain和prompt实现【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
6-13 LCEL记忆的添加方式【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
6-14 LCEL Agents的使用（1）【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
6-15 LCEL Agents的使用（2）【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
6-16 最佳开发实践【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
6-17 本章小结【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
第07章 AI Agent智能体开发：工善其事，必利其器，一步步教你搭建agent开发环境
07-01 本章介绍【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
07-02 虚拟项目demo演示【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
07-03 虚拟项目产品需求分析【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
07-04 虚拟项目技术架构【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
07-05 项目开发环境搭建【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
07-06 本章小结【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
第08章 AI Agent智能体开发：API层的实现以及智能体性格和行为设计
08-01 本章介绍【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
08-02 使用fastapi搭建API层【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
08-03 主Class与agent框架【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
08-04 使用prompt设计agent性格与行为【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
08-05 使用chain来判断输入情绪【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
08-06 langserve介绍【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
08-07 本章小结【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
第09章 AI Agent智能体开发：快速掌握tool以及向量数据库使用
09-01 本章介绍.mp4【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
09-02 tools设计实现1【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
09-03 tools设计实现2【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
09-04 tools设计实施3【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
09-05 agent的memory处理1【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
09-06 agent的memory处理2【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
09-07 agent学习能力构建【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
09-08 本章小结【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
第10章 AI Agent智能体开发：让Agent具备语音能力
10-01 本章介绍【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
10-02 语音逻辑设计【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
10-03 微软TTS能力介绍【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
10-04 -1 voice函数的实现【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
10-05 -2 voice函数的实现【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
10-06 AI语音克隆和TTS介绍【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
10-07 本章小结【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
第11章 AI Agent智能体开发：项目扩展与集成【数字人与IM集成】
11-01 本章介绍【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
11-02 电报机器人+agent的实现【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
11-03 Docker部署与调试追踪【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
11-04 项目扩展：agent数字人（1）【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
11-05 项目扩展：agent数字人（2）【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
11-06 项目扩展：agent数字人（3）【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
11-07 项目扩展：agent数字人（4）【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
11-08 项目扩展：agent数字人（5）【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
11-09 项目扩展：agent数字人（6）【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
11-10 本章小结【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
第12章 课程总结
12-01 课程总结【 微信：itcodeba 】(更多IT教程 www.todo1024.com).mp4
999-【机构课程2】
001-课程介绍.mp4
002-1-Agent要解决的问题分析.mp4
003-2-Agent需要具备的基本能力.mp4
004-3-与大模型的关系分析.mp4
005-4-多智能体定义分析.mp4
006-5-框架的作用和能解决的问题.mp4
007-6-整体总结分析.mp4
008-7-GPTS分析一波.mp4
009-8-经典任务分析.mp4
010-1-GPTS任务流程概述分析.mp4
011-2-调用API的控制方式.mp4
012-3-API相关配置完成.mp4
013-4-完成指令与脚本并生成.mp4
014-1-DEMO演示与整体架构分析.mp4
015-2-后端GPT项目部署启动.mp4
016-3-前端助手API与流程图配置.mp4
017-4-接入外部API的方法与流程.mp4
018-5-GPT中加入外部API调用方法.mp4
019-6-指令提示构建.mp4
020-1-论文概述分析.mp4
021-2-整体框架逻辑介绍.mp4
022-3-项目环境配置.mp4
023-4-基础解读-动作定义方式.mp4
024-5-基础解读-角色定义.mp4
025-6-单动作智能体实现方法.mp4
026-7-多动作配置方法.mp4
027-8-定时器任务环境配置.mp4
028-9-定时器任务流程解读分析.mp4
029-0-基本Agent的组成.mp4
030-1-Agent要完成的任务和业务逻辑定义.mp4
031-2-问题拆解与执行流程.mp4
032-3-检索得到重要的URL.mp4
033-4-子问题生成总结结果.mp4
034-5-总结与结果输出.mp4
035-1-RAG要完成的任务解读.mp4
036-2-RAG整体流程解读.mp4
037-3-召回优化策略分析.mp4
038-4-召回改进方案解读.mp4
039-5-评估工具RAGAS.mp4
040-6-外接本地数据库工具.mp4
041-1-整体故事解读.mp4
042-2-要解决的问题和整体框架分析.mp4
043-3-论文基本框架分析.mp4
044-4-Agent的记忆信息.mp4
045-5-感知与反思模块构建流程.mp4
046-6-计划模块实现细节.mp4
047-7-整体流程框架图.mp4
048-8-感知模块解读.mp4
049-9-思考模块解读.mp4
050-10-项目环境配置方法解读.mp4
051-1-langchain框架解读.mp4
052-2-基本API调用方法.mp4
053-3-数据文档切分操作.mp4
054-4-样本索引与向量构建.mp4
055-5-数据切块方法.mp4
056-1-MOE概述分析.mp4
057-2-MOE模块实现方法解读.mp4
058-3-效果分析与总结.mp4
059-1-大模型如何做下游任务.mp4
060-2-LLM落地微调分析.mp4
061-3-LLAMA与LORA介绍.mp4
062-4-LORA微调的核心思想.mp4
063-5-LORA模型实现细节.mp4
064-1-提示工程的作用.mp4
065-2-项目数据解读.mp4
066-3-源码调用DEBUG解读.mp4
067-4-训练流程演示.mp4
068-5-效果演示与总结分析.mp4
069-1-RAG与微调可以解决与无法解决的问题.mp4
070-2-RAG实践策略.mp4
071-3-微调要解决的问题.mp4
主流Agent项目汇总.pdf
LLM全教程总结.pdf
OpenAI GPT开发资料
openAI 开发教程.zip
微软官方GPT4测评报告 英文.pdf
其他资料
大模型剪枝-模型压缩
2310.06694.pdf
LLM-Shearing-main.zip
介绍.pdf
现有开源的数据集.pdf
选学-prompt工程
OpenAI的官方Prompt工程指南详解.pdf
选学-向量数据库
1-向量数据库介绍 Vector和Embedding关系.mp4
2-向量数据库的功能、特性、发展和基本原理.mp4
3-向量数据库的技术与混合搜索系统.mp4
4-RAG技术详解、向量数据库对大模型的作用.mp4
5-向量数据库核心之相似性搜索.mp4
选学-大模型评估
promptbench-大模型评估框架（微软出品）
promptbench-main.zip
视频讲解.mp4
论文原文.pdf
选学-大模型集群
1-大模型整体架构.mp4
2-大模型全流程介绍.mp4
3-大模型训练效率计算.mp4
4-AI集群硬件组成.mp4
5-集群的分布式架构.mp4
6-大模型训练显存分析.mp4
7-大模型推理显存分析.mp4
学习指南（务必看一下）.pdf
推荐读物
6G内生AI架构及AI大模型.pdf
66个ChatGPT副业赚钱技巧.pdf
AIGC人才趋势洞察报告-猎聘.pdf
ChatGPT 调研报告 (哈尔滨工业大学自然语言处理研究所) (Z-Library).pdf
GPT-5_你需要知道的一切.pdf
PyTorch模型训练调优&GPU并行加速宝典.pdf
transformer系列论文.zip
《大型语言模型中的事实性研究》综述
LLM-Factuality-Survey-main.zip
大模型如何处理事实？西湖大学等最新《大型语言模型中的事实性研究》综述，详述_LLM的知识、检索与领域特异性.pdf
《大语言模型》.pdf
《年中国AI大模型产业发展报告》.pdf
《知识图谱与大模型融合实践研究报告》.pdf
【Air Street Capital】年AI现状报告.pdf
中国大模型发展白皮书.pdf
中国大模型市场商业化进展研究报告.pdf
亚信科技清华大学年AIGCGPT-4赋能通信行业应用白皮书132页.pdf
多态大模型平台的应用研发与思考.pdf
多模态持续预训练实用指南-英文
中文介绍.pdf
文章.pdf
多模态系列论文.zip
大模型综述 97页 英文版.pdf
大语言模型 电子书.pdf
大语言模型在推荐系统的实践应用.pdf
如何选择大模型 英文综述.pdf
年 【100页】从CHAT-GPT到生成式AI(Generative AI)：人工智能新范式，重新定义生产力.pdf
年中国AIGC产业全景报告.pdf
年中国AIGC产业算力发展报告.pdf
推荐系统&大模型.pdf
清华AIGC和ChatGPT报告-192页.pdf
自然语言处理白皮书&发展现状.pdf
！推荐 《ChatGPT：读懂人工智能新纪元》.pdf
！推荐 大规模语言模型-从理论到实践.pdf
01_尚硅谷大模型技术之Python基础
1.笔记
Python连接外部数据源.docx
尚硅谷大模型技术之Python1.0.docx
尚硅谷大模型技术之Python课后练习题以及答案.docx
尚硅谷大模型技术之Python课后练习题无答案.docx
2.资料
Python-3.12.8.tgz
jetbrains
mac
mac-(一键激活)
active-agt.jar
clion.key
clion.sh
config
dns(1).conf
dns.conf
power(1).conf
power.conf
url(1).conf
url.conf
datagrip(1).key
datagrip(1).sh
datagrip.key
datagrip.sh
dataspell(1).key
dataspell(1).sh
dataspell.key
dataspell.sh
goland(1).key
goland(1).sh
goland.key
goland.sh
idea(1).key
idea(1).sh
idea.key
idea.sh
phpstorm(1).key
phpstorm(1).sh
phpstorm.key
phpstorm.sh
plugins
dns(1).jar
dns.jar
hideme(1).jar
hideme.jar
power(1).jar
power.jar
url(1).jar
url.jar
pycharm(1).key
pycharm(1).sh
pycharm.key
pycharm.sh
rider(1).key
rider(1).sh
rider.key
rider.sh
webstorm(1).key
webstorm(1).sh
webstorm.key
webstorm.sh
操作文档(1).pdf
操作文档.pdf
各类计算机课程（java,python,c++,linux网络安全，嵌入式等等）(1).txt
各类计算机课程（java,python,c++,linux网络安全，嵌入式等等）.txt
备用激活
mac-
Activation_Code
AppCode(1).txt
AppCode.txt
CLion(1).txt
CLion.txt
DataGrip(1).txt
DataGrip.txt
DataSpell(1).txt
DataSpell.txt
GoLand(1).txt
GoLand.txt
IntelliJ IDEA(1).txt
IntelliJ IDEA.txt
PhpStorm(1).txt
PhpStorm.txt
PyCharm(1).txt
PyCharm.txt
Rider(1).txt
Rider.txt
RubyMine(1).txt
RubyMine.txt
WebStorm(1).txt
WebStorm.txt
dotCover(1).txt
dotCover.txt
dotMemory(1).txt
dotMemory.txt
dotTrace(1).txt
dotTrace.txt
config-jetbrains
dns(1).conf
dns.conf
power(1).conf
power.conf
url(1).conf
url.conf
ja-netfilter(1).jar
ja-netfilter.jar
plugins-jetbrains
dns(1).jar
dns.jar
hideme.jar
power(1).jar
power.jar
url(1).jar
url.jar
scripts
install(1).sh
install.sh
uninstall(1).sh
uninstall.sh
vmoptions
appcode(1).vmoptions
appcode.vmoptions
clion(1).vmoptions
clion.vmoptions
datagrip(1).vmoptions
datagrip.vmoptions
dataspell(1).vmoptions
dataspell.vmoptions
devecostudio(1).vmoptions
devecostudio.vmoptions
gateway(1).vmoptions
gateway.vmoptions
goland(1).vmoptions
goland.vmoptions
idea(1).vmoptions
idea.vmoptions
jetbrains_client(1).vmoptions
jetbrains_client.vmoptions
jetbrainsclient(1).vmoptions
jetbrainsclient.vmoptions
phpstorm(1).vmoptions
phpstorm.vmoptions
pycharm(1).vmoptions
pycharm.vmoptions
rider(1).vmoptions
rider.vmoptions
rubymine(1).vmoptions
rubymine.vmoptions
studio(1).vmoptions
studio.vmoptions
webide(1).vmoptions
webide.vmoptions
webstorm(1).vmoptions
webstorm.vmoptions
各类计算机课程（java,python,c++,linux网络安全，嵌入式等等）(1).txt
各类计算机课程（java,python,c++,linux网络安全，嵌入式等等）.txt
操作教程(1).pdf
操作教程.pdf
windows
win-(一键激活)pro
CLion激活(1).vbs
CLion激活.vbs
DataGrip激活(1).vbs
DataGrip激活.vbs
DataSpell激活(1).vbs
DataSpell激活.vbs
GoLand激活(1).vbs
GoLand激活.vbs
IDEA激活(1).vbs
IDEA激活.vbs
PhpStorm激活(1).vbs
PhpStorm激活.vbs
PyCharm激活(1).vbs
PyCharm激活.vbs
Rider激活(1).vbs
Rider激活.vbs
WebStorm激活(1).vbs
WebStorm激活.vbs
active-agt(1).jar
active-agt.jar
clion64.exe(1).vmoptions
clion64.exe.vmoptions
clion(1).key
clion.key
config
dns(1).conf
dns.conf
power(1).conf
power.conf
url(1).conf
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datagrip64.exe(1).vmoptions
datagrip64.exe.vmoptions
datagrip(1).key
datagrip.key
dataspell64.exe(1).vmoptions
dataspell64.exe.vmoptions
dataspell(1).key
dataspell.key
goland64.exe(1).vmoptions
goland64.exe.vmoptions
goland(1).key
goland.key
idea64.exe(1).vmoptions
idea64.exe.vmoptions
idea(1).key
idea.key
phpstorm64.exe(1).vmoptions
phpstorm64.exe.vmoptions
phpstorm(1).key
phpstorm.key
plugins
dns.jar
hideme(1).jar
hideme.jar
power(1).jar
power.jar
url(1).jar
url.jar
pycharm64.exe(1).vmoptions
pycharm64.exe.vmoptions
pycharm(1).key
pycharm.key
rider64.exe(1).vmoptions
rider64.exe.vmoptions
rider(1).key
rider.key
webstorm64.exe(1).vmoptions
webstorm64.exe.vmoptions
webstorm(1).key
webstorm.key
操作文档(1).pdf
操作文档.pdf
各类计算机课程（java,python,c++,linux网络安全，嵌入式等等）(1).txt
各类计算机课程（java,python,c++,linux网络安全，嵌入式等等）.txt
备用激活
win-pro
win-
Activation_Code
AppCode(1).txt
AppCode.txt
CLion(1).txt
CLion.txt
DataGrip(1).txt
DataGrip.txt
DataSpell(1).txt
DataSpell.txt
GoLand(1).txt
GoLand.txt
IntelliJ IDEA(1).txt
IntelliJ IDEA.txt
PhpStorm(1).txt
PhpStorm.txt
PyCharm(1).txt
PyCharm.txt
Rider(1).txt
Rider.txt
RubyMine(1).txt
RubyMine.txt
WebStorm(1).txt
WebStorm.txt
dotCover(1).txt
dotCover.txt
dotMemory(1).txt
dotMemory.txt
dotTrace(1).txt
dotTrace.txt
config-jetbrains
dns(1).conf
dns.conf
power.conf
url(1).conf
url.conf
ja-netfilter.jar
plugins-jetbrains
dns(1).jar
dns.jar
hideme.jar
power(1).jar
power.jar
url(1).jar
url.jar
scripts
install(1).vbs
install-current-user(1).vbs
install-current-user.vbs
install.vbs
uninstall-all-users(1).vbs
uninstall-all-users.vbs
uninstall-current-user(1).vbs
uninstall-current-user.vbs
vmoptions
appcode(1).vmoptions
appcode.vmoptions
clion(1).vmoptions
clion.vmoptions
datagrip(1).vmoptions
datagrip.vmoptions
dataspell(1).vmoptions
dataspell.vmoptions
devecostudio(1).vmoptions
devecostudio.vmoptions
gateway(1).vmoptions
gateway.vmoptions
goland(1).vmoptions
goland.vmoptions
idea(1).vmoptions
idea.vmoptions
jetbrains_client(1).vmoptions
jetbrains_client.vmoptions
jetbrainsclient(1).vmoptions
jetbrainsclient.vmoptions
phpstorm(1).vmoptions
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pycharm(1).vmoptions
pycharm.vmoptions
rider(1).vmoptions
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rubymine(1).vmoptions
rubymine.vmoptions
studio(1).vmoptions
studio.vmoptions
webide(1).vmoptions
webide.vmoptions
webstorm(1).vmoptions
webstorm.vmoptions
各类计算机课程（java,python,c++,linux网络安全，嵌入式等等）(1).txt
各类计算机课程（java,python,c++,linux网络安全，嵌入式等等）.txt
操作教程(1).pdf
操作教程.pdf
汉化教程
汉化教程(1).pdf
汉化教程.pdf
说明(1).txt
说明.txt
！！！重要！！！激活教程(1).docx
！！！重要！！！激活教程.docx
jetbrains.zip
pycharm-professional-.3.1.1.exe
pycharm.txt
python-3.12.8-amd64.exe
画图截图工具
Snipaste-2.2.1-Beta2-x64.rar
balsamiqmockupspro.rar
3.代码
3.代码.zip
3.����
Hello
Hello.py
Python����.bmpr
python-250319
01
P01_HelloWorld.py
P02_zs.py
P03_Var.py
readme.txt
.idea
.gitignore
inspectionProfiles
profiles_settings.xml
misc.xml
modules.xml
python-250319.iml
workspace.xml
.venv
.gitignore
Lib
site-packages
__pycache__
_virtualenv.cpython-312.pyc
_virtualenv.pth
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pip
__init__.py
__main__.py
__pip-runner__.py
_internal
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cache.py
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__init__.py
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command_context.py
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distributions
__init__.py
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sdist.py
wheel.py
exceptions.py
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sources.py
locations
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models
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link.py
scheme.py
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selection_prefs.py
target_python.py
wheel.py
network
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auth.py
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lazy_wheel.py
session.py
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build
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metadata.py
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metadata_legacy.py
wheel.py
wheel_editable.py
wheel_legacy.py
check.py
freeze.py
install
__init__.py
editable_legacy.py
wheel.py
prepare.py
pyproject.py
req
__init__.py
constructors.py
req_file.py
req_install.py
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req_uninstall.py
resolution
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base.py
legacy
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resolvelib
__init__.py
base.py
candidates.py
factory.py
found_candidates.py
provider.py
reporter.py
requirements.py
resolver.py
self_outdated_check.py
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__init__.py
_jaraco_text.py
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appdirs.py
compat.py
compatibility_tags.py
datetime.py
deprecation.py
direct_url_helpers.py
egg_link.py
encoding.py
entrypoints.py
filesystem.py
filetypes.py
glibc.py
hashes.py
inject_securetransport.py
logging.py
misc.py
models.py
packaging.py
setuptools_build.py
subprocess.py
temp_dir.py
unpacking.py
urls.py
virtualenv.py
wheel.py
vcs
__init__.py
bazaar.py
git.py
mercurial.py
subversion.py
versioncontrol.py
wheel_builder.py
_vendor
__init__.py
cachecontrol
__init__.py
_cmd.py
adapter.py
cache.py
caches
__init__.py
file_cache.py
redis_cache.py
compat.py
controller.py
filewrapper.py
heuristics.py
serialize.py
wrapper.py
certifi
__init__.py
__main__.py
cacert.pem
core.py
chardet
__init__.py
big5freq.py
big5prober.py
chardistribution.py
charsetgroupprober.py
charsetprober.py
cli
__init__.py
chardetect.py
codingstatemachine.py
codingstatemachinedict.py
cp949prober.py
enums.py
escprober.py
escsm.py
eucjpprober.py
euckrfreq.py
euckrprober.py
euctwfreq.py
euctwprober.py
gb2312freq.py
gb2312prober.py
hebrewprober.py
jisfreq.py
johabfreq.py
johabprober.py
jpcntx.py
langbulgarianmodel.py
langgreekmodel.py
langhebrewmodel.py
langhungarianmodel.py
langrussianmodel.py
langthaimodel.py
langturkishmodel.py
latin1prober.py
macromanprober.py
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mbcsgroupprober.py
mbcssm.py
metadata
__init__.py
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resultdict.py
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sjisprober.py
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version.py
colorama
__init__.py
ansi.py
ansitowin32.py
initialise.py
tests
__init__.py
ansi_test.py
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initialise_test.py
isatty_test.py
utils.py
winterm_test.py
win32.py
winterm.py
distlib
__init__.py
compat.py
database.py
index.py
locators.py
manifest.py
markers.py
metadata.py
resources.py
scripts.py
t32.exe
t64-arm.exe
t64.exe
util.py
version.py
w32.exe
w64-arm.exe
w64.exe
wheel.py
distro
__init__.py
__main__.py
distro.py
idna
__init__.py
codec.py
compat.py
core.py
idnadata.py
intranges.py
package_data.py
uts46data.py
msgpack
__init__.py
exceptions.py
ext.py
fallback.py
packaging
__about__.py
__init__.py
_manylinux.py
_musllinux.py
_structures.py
markers.py
requirements.py
specifiers.py
tags.py
utils.py
version.py
pkg_resources
__init__.py
platformdirs
__init__.py
__main__.py
android.py
api.py
macos.py
unix.py
version.py
windows.py
pygments
__init__.py
__main__.py
cmdline.py
console.py
filter.py
filters
__init__.py
formatter.py
formatters
__init__.py
_mapping.py
bbcode.py
groff.py
html.py
img.py
irc.py
latex.py
other.py
pangomarkup.py
rtf.py
svg.py
terminal256.py
terminal.py
lexer.py
lexers
__init__.py
_mapping.py
python.py
modeline.py
plugin.py
regexopt.py
scanner.py
sphinxext.py
style.py
styles
__init__.py
token.py
unistring.py
util.py
pyparsing
__init__.py
actions.py
common.py
core.py
diagram
__init__.py
exceptions.py
helpers.py
results.py
testing.py
unicode.py
util.py
pyproject_hooks
__init__.py
_compat.py
_impl.py
_in_process
__init__.py
_in_process.py
requests
__init__.py
__version__.py
_internal_utils.py
adapters.py
api.py
auth.py
certs.py
compat.py
cookies.py
exceptions.py
help.py
hooks.py
models.py
packages.py
sessions.py
status_codes.py
structures.py
utils.py
resolvelib
__init__.py
compat
__init__.py
collections_abc.py
providers.py
reporters.py
resolvers.py
structs.py
rich
__init__.py
__main__.py
_cell_widths.py
_emoji_codes.py
_emoji_replace.py
_export_format.py
_extension.py
_fileno.py
_inspect.py
_log_render.py
_loop.py
_null_file.py
_palettes.py
_pick.py
_ratio.py
_spinners.py
_stack.py
_timer.py
_win32_console.py
_windows.py
_windows_renderer.py
_wrap.py
abc.py
align.py
ansi.py
bar.py
box.py
cells.py
color.py
color_triplet.py
columns.py
console.py
constrain.py
containers.py
control.py
default_styles.py
diagnose.py
emoji.py
errors.py
file_proxy.py
filesize.py
highlighter.py
json.py
jupyter.py
layout.py
live.py
live_render.py
logging.py
markup.py
measure.py
padding.py
pager.py
palette.py
panel.py
pretty.py
progress.py
progress_bar.py
prompt.py
protocol.py
region.py
repr.py
rule.py
scope.py
screen.py
segment.py
spinner.py
status.py
style.py
styled.py
syntax.py
table.py
terminal_theme.py
text.py
theme.py
themes.py
traceback.py
tree.py
six.py
tenacity
__init__.py
_asyncio.py
_utils.py
after.py
before.py
before_sleep.py
nap.py
retry.py
stop.py
tornadoweb.py
wait.py
tomli
__init__.py
_parser.py
_re.py
_types.py
typing_extensions.py
urllib3
__init__.py
_collections.py
_version.py
connection.py
connectionpool.py
contrib
__init__.py
_appengine_environ.py
_securetransport
__init__.py
bindings.py
low_level.py
appengine.py
ntlmpool.py
pyopenssl.py
securetransport.py
socks.py
exceptions.py
fields.py
filepost.py
packages
__init__.py
backports
__init__.py
makefile.py
weakref_finalize.py
six.py
poolmanager.py
request.py
response.py
util
__init__.py
connection.py
proxy.py
queue.py
request.py
response.py
retry.py
ssl_.py
ssl_match_hostname.py
ssltransport.py
timeout.py
url.py
wait.py
vendor.txt
webencodings
__init__.py
labels.py
mklabels.py
tests.py
x_user_defined.py
py.typed
pip-23.2.1.dist-info
AUTHORS.txt
INSTALLER
LICENSE.txt
METADATA
RECORD
WHEEL
entry_points.txt
top_level.txt
pip-23.2.1.virtualenv
Scripts
activate
activate.bat
activate.fish
activate.nu
activate.ps1
activate_this.py
deactivate.bat
pip3.12.exe
pip3.exe
pip-3.12.exe
pip.exe
pydoc.bat
python.exe
pythonw.exe
pyvenv.cfg
Hello
Hello.py
Python基础.bmpr
python-250319
01
P01_HelloWorld.py
P02_zs.py
P03_Var.py
readme.txt
.idea
.gitignore
inspectionProfiles
profiles_settings.xml
misc.xml
modules.xml
python-250319.iml
workspace.xml
.venv
.gitignore
Lib
site-packages
__pycache__
_virtualenv.cpython-312.pyc
_virtualenv.pth
_virtualenv.py
pip
__init__.py
__main__.py
__pip-runner__.py
_internal
__init__.py
build_env.py
cache.py
cli
__init__.py
autocompletion.py
base_command.py
cmdoptions.py
command_context.py
main.py
main_parser.py
parser.py
progress_bars.py
req_command.py
spinners.py
status_codes.py
commands
__init__.py
cache.py
check.py
completion.py
configuration.py
debug.py
download.py
freeze.py
hash.py
help.py
index.py
inspect.py
install.py
list.py
search.py
show.py
uninstall.py
wheel.py
configuration.py
distributions
__init__.py
base.py
installed.py
sdist.py
wheel.py
exceptions.py
index
__init__.py
collector.py
package_finder.py
sources.py
locations
__init__.py
_distutils.py
_sysconfig.py
base.py
main.py
metadata
__init__.py
_json.py
base.py
importlib
__init__.py
_compat.py
_dists.py
_envs.py
pkg_resources.py
models
__init__.py
candidate.py
direct_url.py
format_control.py
index.py
installation_report.py
link.py
scheme.py
search_scope.py
selection_prefs.py
target_python.py
wheel.py
network
__init__.py
auth.py
cache.py
download.py
lazy_wheel.py
session.py
utils.py
xmlrpc.py
operations
__init__.py
build
__init__.py
build_tracker.py
metadata.py
metadata_editable.py
metadata_legacy.py
wheel.py
wheel_editable.py
wheel_legacy.py
check.py
freeze.py
install
__init__.py
editable_legacy.py
wheel.py
prepare.py
pyproject.py
req
__init__.py
constructors.py
req_file.py
req_install.py
req_set.py
req_uninstall.py
resolution
__init__.py
base.py
legacy
__init__.py
resolver.py
resolvelib
__init__.py
base.py
candidates.py
factory.py
found_candidates.py
provider.py
reporter.py
requirements.py
resolver.py
self_outdated_check.py
utils
__init__.py
_jaraco_text.py
_log.py
appdirs.py
compat.py
compatibility_tags.py
datetime.py
deprecation.py
direct_url_helpers.py
egg_link.py
encoding.py
entrypoints.py
filesystem.py
filetypes.py
glibc.py
hashes.py
inject_securetransport.py
logging.py
misc.py
models.py
packaging.py
setuptools_build.py
subprocess.py
temp_dir.py
unpacking.py
urls.py
virtualenv.py
wheel.py
vcs
__init__.py
bazaar.py
git.py
mercurial.py
subversion.py
versioncontrol.py
wheel_builder.py
_vendor
__init__.py
cachecontrol
__init__.py
_cmd.py
adapter.py
cache.py
caches
__init__.py
file_cache.py
redis_cache.py
compat.py
controller.py
filewrapper.py
heuristics.py
serialize.py
wrapper.py
certifi
__init__.py
__main__.py
cacert.pem
core.py
chardet
__init__.py
big5freq.py
big5prober.py
chardistribution.py
charsetgroupprober.py
charsetprober.py
cli
__init__.py
chardetect.py
codingstatemachine.py
codingstatemachinedict.py
cp949prober.py
enums.py
escprober.py
escsm.py
eucjpprober.py
euckrfreq.py
euckrprober.py
euctwfreq.py
euctwprober.py
gb2312freq.py
gb2312prober.py
hebrewprober.py
jisfreq.py
johabfreq.py
johabprober.py
jpcntx.py
langbulgarianmodel.py
langgreekmodel.py
langhebrewmodel.py
langhungarianmodel.py
langrussianmodel.py
langthaimodel.py
langturkishmodel.py
latin1prober.py
macromanprober.py
mbcharsetprober.py
mbcsgroupprober.py
mbcssm.py
metadata
__init__.py
languages.py
resultdict.py
sbcharsetprober.py
sbcsgroupprober.py
sjisprober.py
universaldetector.py
utf8prober.py
utf1632prober.py
version.py
colorama
__init__.py
ansi.py
ansitowin32.py
initialise.py
tests
__init__.py
ansi_test.py
ansitowin32_test.py
initialise_test.py
isatty_test.py
utils.py
winterm_test.py
win32.py
winterm.py
distlib
__init__.py
compat.py
database.py
index.py
locators.py
manifest.py
markers.py
metadata.py
resources.py
scripts.py
t32.exe
t64-arm.exe
t64.exe
util.py
version.py
w32.exe
w64-arm.exe
w64.exe
wheel.py
distro
__init__.py
__main__.py
distro.py
idna
__init__.py
codec.py
compat.py
core.py
idnadata.py
intranges.py
package_data.py
uts46data.py
msgpack
__init__.py
exceptions.py
ext.py
fallback.py
packaging
__about__.py
__init__.py
_manylinux.py
_musllinux.py
_structures.py
markers.py
requirements.py
specifiers.py
tags.py
utils.py
version.py
pkg_resources
__init__.py
platformdirs
__init__.py
__main__.py
android.py
api.py
macos.py
unix.py
version.py
windows.py
pygments
__init__.py
__main__.py
cmdline.py
console.py
filter.py
filters
__init__.py
formatter.py
formatters
__init__.py
_mapping.py
bbcode.py
groff.py
html.py
img.py
irc.py
latex.py
other.py
pangomarkup.py
rtf.py
svg.py
terminal256.py
terminal.py
lexer.py
lexers
__init__.py
_mapping.py
python.py
modeline.py
plugin.py
regexopt.py
scanner.py
sphinxext.py
style.py
styles
__init__.py
token.py
unistring.py
util.py
pyparsing
__init__.py
actions.py
common.py
core.py
diagram
__init__.py
exceptions.py
helpers.py
results.py
testing.py
unicode.py
util.py
pyproject_hooks
__init__.py
_compat.py
_impl.py
_in_process
__init__.py
_in_process.py
requests
__init__.py
__version__.py
_internal_utils.py
adapters.py
api.py
auth.py
certs.py
compat.py
cookies.py
exceptions.py
help.py
hooks.py
models.py
packages.py
sessions.py
status_codes.py
structures.py
utils.py
resolvelib
__init__.py
compat
__init__.py
collections_abc.py
providers.py
reporters.py
resolvers.py
structs.py
rich
__init__.py
__main__.py
_cell_widths.py
_emoji_codes.py
_emoji_replace.py
_export_format.py
_extension.py
_fileno.py
_inspect.py
_log_render.py
_loop.py
_null_file.py
_palettes.py
_pick.py
_ratio.py
_spinners.py
_stack.py
_timer.py
_win32_console.py
_windows.py
_windows_renderer.py
_wrap.py
abc.py
align.py
ansi.py
bar.py
box.py
cells.py
color.py
color_triplet.py
columns.py
console.py
constrain.py
containers.py
control.py
default_styles.py
diagnose.py
emoji.py
errors.py
file_proxy.py
filesize.py
highlighter.py
json.py
jupyter.py
layout.py
live.py
live_render.py
logging.py
markup.py
measure.py
padding.py
pager.py
palette.py
panel.py
pretty.py
progress.py
progress_bar.py
prompt.py
protocol.py
region.py
repr.py
rule.py
scope.py
screen.py
segment.py
spinner.py
status.py
style.py
styled.py
syntax.py
table.py
terminal_theme.py
text.py
theme.py
themes.py
traceback.py
tree.py
six.py
tenacity
__init__.py
_asyncio.py
_utils.py
after.py
before.py
before_sleep.py
nap.py
retry.py
stop.py
tornadoweb.py
wait.py
tomli
__init__.py
_parser.py
_re.py
_types.py
typing_extensions.py
urllib3
__init__.py
_collections.py
_version.py
connection.py
connectionpool.py
contrib
__init__.py
_appengine_environ.py
_securetransport
__init__.py
bindings.py
low_level.py
appengine.py
ntlmpool.py
pyopenssl.py
securetransport.py
socks.py
exceptions.py
fields.py
filepost.py
packages
__init__.py
backports
__init__.py
makefile.py
weakref_finalize.py
six.py
poolmanager.py
request.py
response.py
util
__init__.py
connection.py
proxy.py
queue.py
request.py
response.py
retry.py
ssl_.py
ssl_match_hostname.py
ssltransport.py
timeout.py
url.py
wait.py
vendor.txt
webencodings
__init__.py
labels.py
mklabels.py
tests.py
x_user_defined.py
py.typed
pip-23.2.1.dist-info
AUTHORS.txt
INSTALLER
LICENSE.txt
METADATA
RECORD
WHEEL
entry_points.txt
top_level.txt
pip-23.2.1.virtualenv
Scripts
activate
activate.bat
activate.fish
activate.nu
activate.ps1
activate_this.py
deactivate.bat
pip3.12.exe
pip3.exe
pip-3.12.exe
pip.exe
pydoc.bat
python.exe
pythonw.exe
pyvenv.cfg
4.视频
01
00_AI大模型之Python基础_课程介绍.mp4
01_AI大模型之Python基础_计算机组成.mp4
02_AI大模型之Python基础_计算机发展以及语言发展.mp4
03_AI大模型之Python基础_计算机语言发展画图说明.mp4
04_AI大模型之Python基础_编译型语言和解释型语言.mp4
05_AI大模型之Python基础_Python语言的运行方式.mp4
06_AI大模型之Python基础_Python语言特点.mp4
07_AI大模型之Python基础_Python解释器介绍.mp4
08_AI大模型之Python基础_Python的安装.mp4
09_AI大模型之Python基础_卸载问题说明.mp4
10_AI大模型之Python基础_PyCharm的安装.mp4
11_AI大模型之Python基础_科学使用PyCharm.mp4
12_AI大模型之Python基础_Pycharm的设置.mp4
13_AI大模型之Python基础_交互式命令行方式运行程序.mp4
14_AI大模型之Python基础_脚本方式运行程序.mp4
15_AI大模型之Python基础_PyCharm破解问题说明.mp4
16_AI大模型之Python基础_通过PyCharm运行程序.mp4
17_AI大模型之Python基础_注释.mp4
18_AI大模型之Python基础_变量的声明和赋值.mp4
19_AI大模型之Python基础_标识符的命名.mp4
20_AI大模型之Python基础_变量的修改以及常量.mp4
21_AI大模型之Python基础_总结.mp4
02
00_AI大模型之Python基础_内容回顾.mp4
01_AI大模型之Python基础_常见的进制介绍.mp4
02_AI大模型之Python基础_不同进制的表现形式.mp4
03_AI大模型之Python基础_二进制和十进制之间的转换.mp4
04_AI大模型之Python基础_十六进制（八进制）和十进制之间的转换.mp4
05_AI大模型之Python基础_二进制和十六进制之间的转换.mp4
06_AI大模型之Python基础_原码、反码、补码概念.mp4
07_AI大模型之Python基础_计算机为什么使用补码.mp4
08_AI大模型之Python基础_计算机减法转加法思路.mp4
09_AI大模型之Python基础_补码计算原理说明.mp4
10_AI大模型之Python基础_数据类型分类.mp4
11_AI大模型之Python基础_整数类型.mp4
12_AI大模型之Python基础_上午内容回顾.mp4
13_AI大模型之Python基础_浮点数类型.mp4
14_AI大模型之Python基础_布尔类型.mp4
15_AI大模型之Python基础_字符串类型-笔记.PanD
15_AI大模型之Python基础_字符串类型.mp4
16_AI大模型之Python基础_自动类型转换.mp4
17_AI大模型之Python基础_强制类型转换.mp4
18_AI大模型之Python基础_编码和解码.mp4
19_AI大模型之Python基础_input输入.mp4
20_AI大模型之Python基础_普通输出和字符串中使用%占位.mp4
21_AI大模型之Python基础_字符串的format方法.mp4
22_AI大模型之Python基础_f加字符串输出.mp4
23_AI大模型之Python基础_总结.mp4
代码.zip
03
00_AI大模型之Python基础_内容回顾.mp4
01_AI大模型之Python基础_算术、赋值运算符.mp4
02_AI大模型之Python基础_问题解答.mp4
03_AI大模型之Python基础_比较、逻辑运算符.mp4
04_AI大模型之Python基础_位运算符.mp4
05_AI大模型之Python基础_问题解答.mp4
06_AI大模型之Python基础_成员、身份运算符.mp4
07_AI大模型之Python基础_Python编码规范.mp4
08_AI大模型之Python基础_流程控制语句单分支介绍.mp4
09_AI大模型之Python基础_单分支if.mp4
10_AI大模型之Python基础_双分支.mp4
11_AI大模型之Python基础_多分支.mp4
12_AI大模型之Python基础_多分支案例.mp4
13_AI大模型之Python基础_嵌套分支.mp4
14_AI大模型之Python基础_match-case.mp4
15_AI大模型之Python基础_三目运算符.mp4
16_AI大模型之Python基础_while循环.mp4
17_AI大模型之Python基础_while打印进度条.mp4
18_AI大模型之Python基础_whileElse.mp4
19_AI大模型之Python基础_总结以及作业布置.mp4
代码
P01_Operator.py
P02_If.py
P03_IfElse.py
P04_MultiIf.py
P05_NestIf.py
P06_MatchCase.py
P07_Sanm.py
P08_While.py
readme.txt
代码.zip
每日一考
大模型之Python基础-Day01每日一考.md
大模型之Python基础-Day02每日一考.md
大模型之Python基础-Day03每日一考_问题及答案
大模型之Python基础-Day03每日一考_question.md
大模型之Python基础-Day03每日一考answer.md
04
00_AI大模型之Python基础_作业题讲解.mp4
01_AI大模型之Python基础_内容回顾.mp4
02_AI大模型之Python基础_for循环语法介绍.mp4
03_AI大模型之Python基础_for循环遍历案例.mp4
03每日一考.md
04_AI大模型之Python基础_range函数说明.mp4
05_AI大模型之Python基础_循环的嵌套.mp4
06_AI大模型之Python基础_continue、break、pass关键字以及else语句.mp4
07_AI大模型之Python基础_上午内容回顾.mp4
08_AI大模型之Python基础_序列介绍.mp4
09_AI大模型之Python基础_列表的介绍以及创建.mp4
10_AI大模型之Python基础_列表切片.mp4
11_AI大模型之Python基础_列表中的常用方法1.mp4
12_AI大模型之Python基础_列表的遍历.mp4
13_AI大模型之Python基础_列表中的常用方法2.mp4
14_AI大模型之Python基础_列表推导式.mp4
15_AI大模型之Python基础_列表常用方法3.mp4
代码
P01_Test.py
P02_For.py
P03_Range.py
P04_Nest.py
P05_ContinueAndBreak.py
P06_List.py
P07_List_Ope.py
readme.txt
05
00_AI大模型之Python基础_每日一考讲解.mp4
01_AI大模型之Python基础_字符串介绍.mp4
02_AI大模型之Python基础_字符串基本操作.mp4
03_AI大模型之Python基础_字符串常用函数.mp4
04_AI大模型之Python基础_元组.mp4
05_AI大模型之Python基础_集合基本操作.mp4
06_AI大模型之Python基础_集合常用的函数.mp4
07_AI大模型之Python基础_字典基本介绍.mp4
08_AI大模型之Python基础_字典对象的创建以及访问方式.mp4
09_AI大模型之Python基础_字典的基础操作.mp4
10_AI大模型之Python基础_字典的遍历以及常用函数.mp4
11_AI大模型之Python基础_各个容器类型总结.mp4
代码
P01_Test.py
P02_Str.py
P03_Str_Func.py
P04_Tuple.py
P05_Set.py
P06_Set_Func.py
P07_Dict.py
readme.txt
每日一考.md
06
00_AI大模型之Python基础_内容回顾.mp4
01_AI大模型之Python基础_函数的定义以及为什么抽取函数.mp4
02_AI大模型之Python基础_函数的抽取.mp4
03_AI大模型之Python基础_函数的形参和实参.mp4
04_AI大模型之Python基础_函数执行内存分析.mp4
05_AI大模型之Python基础_传递不可变对象.mp4
06_AI大模型之Python基础_传递可变对象.mp4
07_AI大模型之Python基础_上午内容回顾.mp4
08_AI大模型之Python基础_赋值操作情况说明.mp4
09_AI大模型之Python基础_参数传递的形式.mp4
10_AI大模型之Python基础_解包传参.mp4
11_AI大模型之Python基础_浅拷贝.mp4
12_AI大模型之Python基础_浅拷贝原理图示.mp4
13_AI大模型之Python基础_深拷贝原理图示.mp4
14_AI大模型之Python基础_方法的返回值.mp4
15_AI大模型之Python基础_总结.mp4
代码
P01_No_Func.py
P02_Func.py
P03_Func_Param.py
P04_Param_Pass.py
P05_Param_Pass_Type.py
P06_ChangeList.py
P07_Return.py
readme.txt
每日一考.md
07
00_AI大模型之Python基础_内容回顾.mp4
01_AI大模型之Python基础_考试题讲解.mp4
02_AI大模型之Python基础_函数嵌套调用.mp4
03_AI大模型之Python基础_作用域.mp4
04_AI大模型之Python基础_闭包.mp4
05_AI大模型之Python基础_作用域.mp4
06_AI大模型之Python基础_全局变量和局部变量.mp4
07_AI大模型之Python基础_global和nonlocal关键字.mp4
08_AI大模型之Python基础_函数的递归.mp4
09_AI大模型之Python基础_函数递归调用内存分析.mp4
10_AI大模型之Python基础_匿名函数的定义.mp4
11_AI大模型之Python基础_匿名函数应用.mp4
12_AI大模型之Python基础_匿名函数实现说明.mp4
13_AI大模型之Python基础_函数注释.mp4
14_AI大模型之Python基础_文件操作模式介绍.mp4
15_AI大模型之Python基础_读写数据.mp4
20250326周四考试.md
Python基础.bmpr
代码
P01_Exe.py
P02_Func_Nest.py
P03_Scope.py
P04_Closure.py
P05_GlobalAndLocalVal.py
P06_GlobalAndNonlocal.py
P07_Factorial.py
P08_Anonymity_Function.py
P09_Anonymity_Function_1.py
P10_Func_Anon.py
P11_File.py
readme.txt
test.txt
大模型之Python基础-Day06每日一考.md
08
00_AI大模型之Python基础_内容回顾.mp4
01_AI大模型之Python基础_图片拷贝.mp4
02_AI大模型之Python基础_图片拷贝优化.mp4
03_AI大模型之Python基础_面向过程与面向函数式编程.mp4
04_AI大模型之Python基础_面向对象编程思想.mp4
05_AI大模型之Python基础_类和对象的概念.mp4
06_AI大模型之Python基础_通过类创建对象案例.mp4
07_AI大模型之Python基础_对象创建内存分析.mp4
07_每日一考.md
08_AI大模型之Python基础_补充.mp4
09_AI大模型之Python基础_类的定义以及类的操作.mp4
10_AI大模型之Python基础_init方法.mp4
11_AI大模型之Python基础_self.mp4
12_AI大模型之Python基础_类属性.mp4
13_AI大模型之Python基础_实例属性.mp4
14_AI大模型之Python基础_实例方法和类方法.mp4
15_AI大模型之Python基础_静态方法和特殊方法.mp4
16_AI大模型之Python基础_动态添加属性以及方法.mp4
17_AI大模型之Python基础_总结.mp4
Python基础.bmpr
代码
P01_Ite_File.py
P02_File_Copy.py
P03_OP_OF_OO.py
P04_Class_Demo.py
P05_Class.py
P06_Self.py
P07_Attribute.py
P08_Method.py
P09_Del.py
P10_Slots.py
readme.txt
09
00_AI大模型之Python基础_内容回顾.mp4
01_AI大模型之Python基础_面向对象的三大特性整体介绍.mp4
02_AI大模型之Python基础_私有化属性和方法.mp4
03_AI大模型之Python基础_成员私有化本质.mp4
04_AI大模型之Python基础_@property用法.mp4
05_AI大模型之Python基础_读写属性.mp4
06_AI大模型之Python基础_封装案例.mp4
07_AI大模型之Python基础_上午内容回顾.mp4
08_AI大模型之Python基础_随堂案例.mp4
08_每日一考.md
09_AI大模型之Python基础_单继承案例.mp4
10_AI大模型之Python基础_多继承.mp4
11_AI大模型之Python基础_super方法父类的属性和方法.mp4
12_AI大模型之Python基础_方法调用顺序.mp4
13_AI大模型之Python基础_方法的重写.mp4
14_AI大模型之Python基础_多态.mp4
15_AI大模型之Python基础_总结以及愤怒的小鸟案例说明.mp4
代码
P01_Private.py
P02_Property.py
P03_CreditCard.py
P04_Su7.py
P05_Extend.py
P06_Multi_Extend.py
P07_Super.py
P08_OverWrite.py
P09_Polymorphic.py
readme.txt
10
00_AI大模型之Python基础_习题讲解.mp4
01_AI大模型之Python基础_鸟基类的创建.mp4
02_AI大模型之Python基础_鸟子类的创建.mp4
03_AI大模型之Python基础_障碍物类的创建.mp4
04_AI大模型之Python基础_创建相关对象完成攻击.mp4
05_AI大模型之Python基础_异常处理基本语法.mp4
06_AI大模型之Python基础_捕获不同类型的异常.mp4
07_AI大模型之Python基础_Else语句块.mp4
08_AI大模型之Python基础_Finally.mp4
09_AI大模型之Python基础_Raise抛出异常.mp4
09_每日一考.md
10_AI大模型之Python基础_assert断言机制.mp4
11_AI大模型之Python基础_自定义异常.mp4
12_AI大模型之Python基础_异常的传递.mp4
13_AI大模型之Python基础_With关键字介绍.mp4
14_AI大模型之Python基础_With关键字案例.mp4
15_AI大模型之Python基础_总结.mp4
代码
P01_Game.py
P02_Exception.py
P03_Exception_Type.py
P04_Else.py
P05_Finally.py
P06_Raise.py
P07_assert.py
P08_Custom_Exception.py
P09_Exception_Pass.py
P10_With.py
readme.txt
test.txt
11
00_AI大模型之Python基础_内容回顾.mp4
01_AI大模型之Python基础_模块介绍.mp4
02_AI大模型之Python基础_全局导入模块.mp4
03_AI大模型之Python基础_局部导入模块情况1.mp4
04_AI大模型之Python基础_局部导入模块情况2.mp4
05_AI大模型之Python基础_模块搜索顺序.mp4
06_AI大模型之Python基础___all__限制导入成员.mp4
07_AI大模型之Python基础___name__变量.mp4
08_AI大模型之Python基础_dir函数.mp4
09_AI大模型之Python基础_包的创建.mp4
10_AI大模型之Python基础_上午内容回顾.mp4
10_每日一考.md
11_AI大模型之Python基础_带包的全局导入.mp4
12_AI大模型之Python基础_局部导入1.mp4
13_AI大模型之Python基础_局部导入2.mp4
14_AI大模型之Python基础_安装第三方库介绍.mp4
15_AI大模型之Python基础_打包自己开发的代码.mp4
16_AI大模型之Python基础_通过命令的方式安装自己打包的库.mp4
17_AI大模型之Python基础_pycharm界面方式安装自己打包的库.mp4
18_AI大模型之Python基础_总结.mp4
代码
P01_My_Add.py
P02_Main.py
P03_My_Multi.py
P04_Main.py
__pycache__
P01_My_Add.cpython-312.pyc
P03_My_Multi.cpython-312.pyc
graphic
__init__.py
__pycache__
__init__.cpython-312.pyc
circle.cpython-312.pyc
rectangle.cpython-312.pyc
circle.py
rectangle.py
readme.txt
setup.py
12
00_AI大模型之Python基础_内容回顾.mp4
01_AI大模型之Python基础_浅拷贝案例.mp4
02_AI大模型之Python基础_深拷贝案例.mp4
03_AI大模型之Python基础_迭代器介绍.mp4
04_AI大模型之Python基础_通过容器创建迭代器对象.mp4
05_AI大模型之Python基础_自定义迭代器.mp4
06_AI大模型之Python基础_生成器介绍以及斐波那契数列.mp4
07_AI大模型之Python基础_通过函数创建生成器对象.mp4
08_AI大模型之Python基础_通过send向生成器发送数据.mp4
09_AI大模型之Python基础_命名空间.mp4
10_AI大模型之Python基础_四种作用域.mp4
11_AI大模型之Python基础_闭包.mp4
11_每日一考.md
12_AI大模型之Python基础_闭包实现装饰器.mp4
13_AI大模型之Python基础_装饰器语法糖实现装饰器.mp4
14_AI大模型之Python基础_多层装饰器.mp4
15_AI大模型之Python基础_多层装饰器内存图.mp4
16_AI大模型之Python基础_带参数的装饰器.mp4
17_AI大模型之Python基础_类装饰器.mp4
18_AI大模型之Python基础_总结.mp4
Python基础.bmpr
代码
P01_Copy.py
P02_Iterator.py
P03_Generator.py
P04_Scope.py
P05_Enclosing.py
P06_Decorator.py
readme.txt
13
00_AI大模型之Python基础_考题讲解以及内容回顾.mp4
01_AI大模型之Python基础_同步异步以及并发和并行概念.mp4
02_AI大模型之Python基础_多进程以及创建方式说明.mp4
03_AI大模型之Python基础_多进程方式读写文件.mp4
04_AI大模型之Python基础_自定义进程类.mp4
05_AI大模型之Python基础_进程池.mp4
06_AI大模型之Python基础_进程池案例.mp4
07_AI大模型之Python基础_上午内容回顾.mp4
08_AI大模型之Python基础_多进程间不共享全局变量.mp4
09_AI大模型之Python基础_Queue介绍.mp4
10_AI大模型之Python基础_进程间通过Quque共享数据.mp4
11_AI大模型之Python基础_线程相关概念.mp4
12_AI大模型之Python基础_线程对象的创建.mp4
12_每日一考.md
13_AI大模型之Python基础_线程池.mp4
14_AI大模型之Python基础_线程不安全问题说明.mp4
15_AI大模型之Python基础_总结.mp4
代码
P01_math_operations.py
P02_Test.py
P03_Process.py
P04_Custom_Process.py
P05_Process_Pool.py
P06_Process_No_Share.py
P07_Process_Share.py
P08_Thread.py
P09_Custom_Thread.py
P10_Thread_Pool.py
P11_Thread_No_Safe.py
__pycache__
P01_math_operations.cpython-312.pyc
readme.txt
test.py
14
00_AI大模型之Python基础_内容回顾.mp4
01_AI大模型之Python基础_加锁解决线程安全问题.mp4
02_AI大模型之Python基础_进程和线程对比.mp4
03_AI大模型之Python基础_网络相关概念.mp4
04_AI大模型之Python基础_UDP通信介绍.mp4
05_AI大模型之Python基础_UDP开发案例.mp4
06_AI大模型之Python基础_上午内容回顾.mp4
07_AI大模型之Python基础_TCP通信介绍.mp4
08_AI大模型之Python基础_TCP开发案例.mp4
09_AI大模型之Python基础_TCP开发案例优化.mp4
10_AI大模型之Python基础_加入多线程以及异常处理.mp4
11_AI大模型之Python基础_Http以及一言网介绍.mp4
12_AI大模型之Python基础_请求一言网.mp4
13.md
13_AI大模型之Python基础_starlette部署web服务.mp4
14_AI大模型之Python基础_总结.mp4
代码
P01_Thread_Safe.py
P02_UDP_Server.py
P03_UDP_Client.py
P04_TCP_Server.py
P05_TCP_Client.py
P06_Http.py
P07_Starlette.py
__pycache__
P02_UDP_Server.cpython-312.pyc
readme.txt
15
00_AI大模型之Python基础_内容回顾.mp4
01_AI大模型之Python基础_正则表达式介绍.mp4
02_AI大模型之Python基础_正则表达式案例.mp4
03_AI大模型之Python基础_客户管理系统需求介绍.mp4
04_AI大模型之Python基础_创建客户类.mp4
05_AI大模型之Python基础_初始化两个字典用于存放客户信息.mp4
06_AI大模型之Python基础_主菜单页的开发.mp4
07_AI大模型之Python基础_将用户添加到集合中.mp4
08_AI大模型之Python基础_添加用户id.mp4
09_AI大模型之Python基础_添加用户其它功能的实现.mp4
10_AI大模型之Python基础_显示所有用户以及作业布置.mp4
14_每日一考.md
代码
P01_Re.py
__pycache__
customer.cpython-312.pyc
cms.py
customer.py
02_数据结构与算法
1.笔记
尚硅谷大模型技术之数据结构与算法1.0.docx
2.资料
3.代码
4.视频
01
00_AI大模型之数据结构与算法_案例问题说明.mkv
01_AI大模型之数据结构与算法_如何学.mkv
02_AI大模型之数据结构与算法_数据结构分类.mkv
03_AI大模型之数据结构与算法_时间复杂度.mkv
04_AI大模型之数据结构与算法_最坏时间复杂度.mkv
05_AI大模型之数据结构与算法_大O表示法常见的情况.mkv
06_AI大模型之数据结构与算法_空间复杂度.mkv
07_AI大模型之数据结构与算法_数组和list区别.mkv
08_AI大模型之数据结构与算法_自定义数组.mkv
09_AI大模型之数据结构与算法_数组扩容.mkv
10_AI大模型之数据结构与算法_向数组中添加元素.mkv
11_AI大模型之数据结构与算法_上午内容回顾.mp4
12_AI大模型之数据结构与算法_数组的删除以及其它操作.mp4
13_AI大模型之数据结构与算法_数组实现需要注意的问题.mp4
14_AI大模型之数据结构与算法_链表类创建.mp4
15_AI大模型之数据结构与算法_向链表中插入元素.mp4
16_AI大模型之数据结构与算法_删除链表元素.mp4
17_AI大模型之数据结构与算法_链表其它操作.mp4
18_AI大模型之数据结构与算法_总结.mp4
代码
P01_BigO.py
P02_Array.py
P03_LinkedList.py
readme.txt
02
00_AI大模型之数据结构与算法_内容回顾.mp4
01_AI大模型之数据结构与算法_栈数据结构介绍.mp4
02_AI大模型之数据结构与算法_栈数据结构实现.mp4
03_AI大模型之数据结构与算法_栈应用.mp4
04_AI大模型之数据结构与算法_队列介绍.mp4
05_AI大模型之数据结构与算法_入队代码实现.mp4
06_AI大模型之数据结构与算法_出队代码以及队列测试.mp4
07_AI大模型之数据结构与算法_上午内容回顾.mp4
08_AI大模型之数据结构与算法_哈希表介绍.mp4
09_AI大模型之数据结构与算法_哈希表类创建.mp4
10_AI大模型之数据结构与算法_显示哈希表中所有元素.mp4
11_AI大模型之数据结构与算法_向哈希表中添加元素.mp4
12_AI大模型之数据结构与算法_扩容.mp4
13_AI大模型之数据结构与算法_从哈希表中删除元素.mp4
14_AI大模型之数据结构与算法_获取元素以及遍历.mp4
15_AI大模型之数据结构与算法_哈希表整体测试.mp4
16_AI大模型之数据结构与算法_总结.mp4
代码
P01_Stack.py
P02_Stack_Demo.py
P03_Queue.py
P04_HashTable.py
readme.txt
数据结构与算法.bmpr
03
00_AI大模型之数据结构与算法_内容回顾.mp4
01_AI大模型之数据结构与算法_树介绍.mp4
02_AI大模型之数据结构与算法_二叉树的存储方式介绍.mp4
03_AI大模型之数据结构与算法_常见的二叉树.mp4
04_AI大模型之数据结构与算法_常见的二叉树动画演示.mp4
05_AI大模型之数据结构与算法_定义节点类以及树类.mp4
06_AI大模型之数据结构与算法_查询方法的实现.mp4
07_AI大模型之数据结构与算法_向树中添加元素.mp4
08_AI大模型之数据结构与算法_删除元素的几种情况说明.mp4
09_AI大模型之数据结构与算法_删除没有子节点的节点.mp4
10_AI大模型之数据结构与算法_删除只有一个子节点的节点.mp4
11_AI大模型之数据结构与算法_删除有两个子节点的节点.mp4
12_AI大模型之数据结构与算法_上午内容回顾.mp4
13_AI大模型之数据结构与算法_树的遍历.mp4
14_AI大模型之数据结构与算法_图的介绍.mp4
15_AI大模型之数据结构与算法_二分查找法.mp4
16_AI大模型之数据结构与算法_查找多数元素.mp4
17_AI大模型之数据结构与算法_总结.mp4
代码
P01_Binary_Search_Tree.py
readme.txt
04
00_AI大模型之数据结构与算法_内容回顾.mp4
01_AI大模型之数据结构与算法_冒泡排序.mp4
02_AI大模型之数据结构与算法_选择排序.mp4
03_AI大模型之数据结构与算法_插入排序.mp4
04_AI大模型之数据结构与算法_归并排序.mp4
05_AI大模型之数据结构与算法_上午内容回顾.mp4
06_AI大模型之数据结构与算法_快速排序.mp4
07_AI大模型之数据结构与算法_堆排序.mp4
08_AI大模型之数据结构与算法_分治_汉诺塔思路_1.mp4
09_AI大模型之数据结构与算法_分治_汉诺塔思路_2.mp4
代码
P01_Bubble_Sort.py
P02_Select_Sort.py
P03_Insert_Sort.py
P04_Merge_Sort.py
P05_Quick_Sort.py
P06_Heap_Sort.py
P07_Hanota.py
数据结构与算法.bmpr
05
00_AI大模型之数据结构与算法_卡拉楚巴算法.mp4
01_AI大模型之数据结构与算法_卡拉楚巴算法代码分析.mp4
02_AI大模型之数据结构与算法_动态规划爬楼梯.mp4
03_AI大模型之数据结构与算法_最大的连续子数组之和.mp4
04_AI大模型之数据结构与算法_0-1背包思路分析.mp4
05_AI大模型之数据结构与算法_0-1背包代码分析.mp4
06_AI大模型之数据结构与算法_完全背包.mp4
07_AI大模型之数据结构与算法_回溯算法_全排列.mp4
08_AI大模型之数据结构与算法_全排列代码分析.mp4
09_AI大模型之数据结构与算法_贪心算法_最大交换.mp4
代码
P01_Karatsuba.py
P02_climb.py
P03_subarray.py
P04_Knapsack.py
P05_Permute.py
数据结构与算法.bmpr
03_Linux及Shell
1.笔记
尚硅谷大模型技术之Linux（Ubuntu）1.0.docx
尚硅谷大模型技术之Shell1.0.docx
2.资料
VMware 17的许可密钥.txt
VMware-workstation-full-17.5.1-23298084.exe
Xftp-8.0.0068p.exe
Xshell-8.0.0069p.exe
ubuntu-22.04.4-desktop-amd64.iso
4.视频
01
00_AI大模型之Linux与Shell_阶段考试题讲解.mp4
01_AI大模型之Linux与Shell_Linux介绍.mp4
02_AI大模型之Linux与Shell_安装VMWare虚拟机.mp4
03_AI大模型之Linux与Shell_配置虚拟电脑.mp4
04_AI大模型之Linux与Shell_Ubuntu系统安装.mp4
05_AI大模型之Linux与Shell_配置网络.mp4
06_AI大模型之Linux与Shell_安装Xshell并配置连接.mp4
07_AI大模型之Linux与Shell_Xshell版本说明.mp4
08_AI大模型之Linux与Shell_目录结构介绍.mp4
09_AI大模型之Linux与Shell_软件包管理器.mp4
10_AI大模型之Linux与Shell_帮助命令.mp4
11_AI大模型之Linux与Shell_pwd,ls,cd命令.mp4
12_AI大模型之Linux与Shell_mkdir,touch,cp命令.mp4
13_AI大模型之Linux与Shell_rm,mv,cat,tail,echo命令.mp4
14_AI大模型之Linux与Shell_重定向,ln,history命令.mp4
15_AI大模型之Linux与Shell_vim编辑器模式.mp4
16_AI大模型之Linux与Shell_vim演示.mp4
17_AI大模型之Linux与Shell_root用户.mp4
18_AI大模型之Linux与Shell_用户管理命令.mp4
19_AI大模型之Linux与Shell_用户组管理命令.mp4
20_AI大模型之Linux与Shell_文件权限命令.mp4
02
00_AI大模型之Linux与Shell_内容回顾.mp4
01_AI大模型之Linux与Shell_find命令.mp4
02_AI大模型之Linux与Shell_管道符和grep.mp4
03_AI大模型之Linux与Shell_打包和解包.mp4
04_AI大模型之Linux与Shell_df,du,top和free命令.mp4
05_AI大模型之Linux与Shell_ps和netstat命令.mp4
06_AI大模型之Linux与Shell_定时任务.mp4
07_AI大模型之Linux与Shell_Shell介绍.mp4
08_AI大模型之Linux与Shell_第一个Shell程序.mp4
09_AI大模型之Linux与Shell_变量定义.mp4
10_AI大模型之Linux与Shell_特殊变量.mp4
11_AI大模型之Linux与Shell_上午内容回顾.mp4
12_AI大模型之Linux与Shell_算术运算与条件判断.mp4
13_AI大模型之Linux与Shell_if分支.mp4
14_AI大模型之Linux与Shell_case分支.mp4
15_AI大模型之Linux与Shell_for循环.mp4
16_AI大模型之Linux与Shell_特殊变量对比.mp4
17_AI大模型之Linux与Shell_while循环.mp4
18_AI大模型之Linux与Shell_read.mp4
19_AI大模型之Linux与Shell_自定义函数.mp4
20_AI大模型之Linux与Shell_cut命令.mp4
21_AI大模型之Linux与Shell_awk命令.mp4
每日一考.md
04_MySQL
1.笔记
尚硅谷大模型技术之MySQL1.0.docx
2.资料
Navicatls_17.rar
mysql-installer-community-8.0.26.0.msi
演示数据.sql
练习数据.sql
3.代码
4.视频
01
00_AI大模型之MySQL_每日一考讲解.mp4
01_AI大模型之MySQL_MySQL介绍.mp4
02_AI大模型之MySQL_表之间关系.mp4
03_AI大模型之MySQL_MySQL的安装.mp4
04_AI大模型之MySQL_客户端工具的使用.mp4
05_AI大模型之MySQL_命令行客户端基本操作.mp4
06_AI大模型之MySQL_可视化客户端基本操作.mp4
07_AI大模型之MySQL_SQL语句分类以及规范和注释.mp4
08_AI大模型之MySQL_DDL_库相关.mp4
09_AI大模型之MySQL_DDL_创建表.mp4
10_AI大模型之MySQL_DDL_其它表相关操作.mp4
11_AI大模型之MySQL_DML_向表中添加数据.mp4
12_AI大模型之MySQL_DML_从表中删除数据.mp4
13_AI大模型之MySQL_DML_修改表中数据.mp4
14_AI大模型之MySQL_DML_查询以及总结.mp4
15_AI大模型之MySQL_算术、比较、区间运算符.mp4
16_AI大模型之MySQL_模糊匹配.mp4
17_AI大模型之MySQL_逻辑运算以及空值处理.mp4
每日一考.md
02
00_AI大模型之MySQL_内容回顾.mp4
01_AI大模型之MySQL_整数类型.mp4
02_AI大模型之MySQL_浮点数类型.mp4
03_AI大模型之MySQL_定长与变长字符串.mp4
04_AI大模型之MySQL_枚举与集合.mp4
05_AI大模型之MySQL_日期时间类型.mp4
06_AI大模型之MySQL_常用的数学函数.mp4
07_AI大模型之MySQL_常用数学函数案例.mp4
08_AI大模型之MySQL_上午内容回顾.mp4
09_AI大模型之MySQL_常用字符串函数.mp4
10_AI大模型之MySQL_常用字符函数案例.mp4
11_AI大模型之MySQL_日期函数.mp4
12_AI大模型之MySQL_加密函数.mp4
13_AI大模型之MySQL_条件判断函数.mp4
14_AI大模型之MySQL_聚合函数.mp4
15_AI大模型之MySQL_窗口函数.mp4
16_AI大模型之MySQL_分组函数案例.mp4
每日一考.md
03
00_AI大模型之MySQL_内容回顾.mp4
01_AI大模型之MySQL_关联查询介绍.mp4
02_AI大模型之MySQL_内连接.mp4
03_AI大模型之MySQL_左外连接.mp4
04_AI大模型之MySQL_右外连接.mp4
05_AI大模型之MySQL_全外连接.mp4
06_AI大模型之MySQL_自连接.mp4
07_AI大模型之MySQL_from,where,join,groupby子句.mp4
08_AI大模型之MySQL_having,orderby,limit.mp4
09_AI大模型之MySQL_上午内容回顾.mp4
10_AI大模型之MySQL_select子句执行顺序.mp4
11_AI大模型之MySQL_select中使用子查询.mp4
12_AI大模型之MySQL_where中使用子查询.mp4
13_AI大模型之MySQL_having中使用子查询.mp4
14_AI大模型之MySQL_exists子查询.mp4
15_AI大模型之MySQL_from中使用子查询.mp4
16_AI大模型之MySQL_update中使用子查询.mp4
17_AI大模型之MySQL_子查询建表以及通用表达式.mp4
数据结构与算法.bmpr
每日一考.md
04
00_AI大模型之MySQL_内容回顾.mp4
01_AI大模型之MySQL_约束介绍.mp4
02_AI大模型之MySQL_非空约束.mp4
03_AI大模型之MySQL_唯一键索引.mp4
04_AI大模型之MySQL_主键约束.mp4
05_AI大模型之MySQL_自增约束.mp4
06_AI大模型之MySQL_默认值约束.mp4
07_AI大模型之MySQL_检查约束.mp4
08_AI大模型之MySQL_外键约束.mp4
09_AI大模型之MySQL_事务.mp4
10_AI大模型之MySQL_事务隔离级别.mp4
11_AI大模型之MySQL_用户管理.mp4
12_AI大模型之MySQL_从本地MySQL中查询数据.mp4
13_AI大模型之MySQL_添加，修改，删除数据.mp4
14_AI大模型之MySQL_Ubuntu上安装MySQL.mp4
15_AI大模型之MySQL_操作Ubuntu上的MySQL.mp4
16_AI大模型之MySQL_操作Redis.mp4
17_AI大模型之MySQL_操作Hive.mp4
Python连接外部数据源
Hadoop的安装与配置.docx
MySQLl的卸载与安装.docx
Python连接外部数据源.docx
Redis的卸载与安装.docx
apache-hive-3.1.3-bin.tar.gz
hadoop-3.3.4.tar.gz
jdk-8u212-linux-x64.tar.gz
mysql-apt-config_0.8.34-1_all.deb
代码
P01_MySQL.py
P02_Redis.py
P03_Hive.py
每日一考.md
05_Numpy&Pandas
1.笔记
尚硅谷大模型技术之numpy与pandas1.0.docx
2.资料
Anaconda3-.10-1-Linux-x86_64.sh
Anaconda3-.10-1-Windows-x86_64.exe
data
employees.csv
house_sales.csv
penguins.csv
sleep.csv
weather.csv
weather_withna.csv
3.代码
4.视频
01
00_AI大模型之Numpy_Pandas_前面内容梳理.mp4
01_AI大模型之Numpy_Pandas_Anaconda介绍.mp4
02_AI大模型之Numpy_Pandas_Window上安装Anaconda.mp4
03_AI大模型之Numpy_Pandas_Ubuntu上安装Anaconda.mp4
04.md
04_AI大模型之Numpy_Pandas_Pycharm中集成Jupyter.mp4
05_AI大模型之Numpy_Pandas_上午内容回顾.mp4
06_AI大模型之Numpy_Pandas_Pycharm中使用远程Jupyter.mp4
07_AI大模型之Numpy_Pandas_Numpy介绍.mp4
08_AI大模型之Numpy_Pandas_ndArray常用的属性.mp4
09_AI大模型之Numpy_Pandas_array()与asarray().mp4
10_AI大模型之Numpy_Pandas_zeros、ones、empty.mp4
11_AI大模型之Numpy_Pandas_full、arange、linspace、logspace.mp4
12_AI大模型之Numpy_Pandas_随机数数组以及matrix.mp4
13_AI大模型之Numpy_Pandas_ndarray数据类型.mp4
14_AI大模型之Numpy_Pandas_切片和索引.mp4
15_AI大模型之Numpy_Pandas_基本函数.mp4
代码
P01_Test.ipynb
P02_Numpy_Properties.ipynb
P03_NdArray_Create.ipynb
P04_Split.ipynb
02
00_AI大模型之Numpy_Pandas_内容回顾.mp4
01_AI大模型之Numpy_Pandas_统计函数.mp4
02_AI大模型之Numpy_Pandas_比较、排序、去重函数.mp4
03_AI大模型之Numpy_Pandas_广播.mp4
04_AI大模型之Numpy_Pandas_矩阵乘法.mp4
05_AI大模型之Numpy_Pandas_Pandas介绍.mp4
06_AI大模型之Numpy_Pandas_Series对象的创建.mp4
07_AI大模型之Numpy_Pandas_Series常用属性.mp4
08_AI大模型之Numpy_Pandas_Series常用方法_1.mp4
09_AI大模型之Numpy_Pandas_Series常用方式_2.mp4
10_AI大模型之Numpy_Pandas_Series的计算.mp4
11_AI大模型之Numpy_Pandas_DataFrame对象的创建.mp4
12_AI大模型之Numpy_Pandas_DataFrame常用的属性.mp4
代码
P01_Numpy_Function.ipynb
P02_Series.ipynb
P03_DataFrame.ipynb
尚硅谷大模型技术之numpy与pandas1.0.docx
每日一考.md
03
00_AI大模型之Numpy_Pandas_内容回顾.mp4
01_AI大模型之Numpy_Pandas_DataFrame常用方法.mp4
02_AI大模型之Numpy_Pandas_布尔索引以及DataFrame的运算.mp4
03_AI大模型之Numpy_Pandas_DataFrame的修改操作.mp4
04_AI大模型之Numpy_Pandas_数据的导出.mp4
05_AI大模型之Numpy_Pandas_数据的导入以及日期处理初识.mp4
06_AI大模型之Numpy_Pandas_简单数据分析.mp4
07_AI大模型之Numpy_Pandas_分组聚合统计.mp4
08_AI大模型之Numpy_Pandas_员工分析练习.mp4
09_AI大模型之Numpy_Pandas_concat.mp4
10_AI大模型之Numpy_Pandas_merge基本连接.mp4
11_AI大模型之Numpy_Pandas_merge实现内外连接以及join连接.mp4
代码.exe
每日一考.md
04
00_AI大模型之Numpy_Pandas_内容回顾.mp4
01_AI大模型之Numpy_Pandas_查看缺失值.mp4
02_AI大模型之Numpy_Pandas_剔除以及填充缺失值.mp4
03_AI大模型之Numpy_Pandas_Series中使用apply.mp4
04_AI大模型之Numpy_Pandas_DataFrame中使用apply以及向量化函数.mp4
05_AI大模型之Numpy_Pandas_DataFrameGroupBy对象.mp4
06_AI大模型之Numpy_Pandas_cut函数.mp4
07_AI大模型之Numpy_Pandas_上午内容回顾.mp4
08_AI大模型之Numpy_Pandas_分组聚合.mp4
09_AI大模型之Numpy_Pandas_分组转换以及分组过滤.mp4
10_AI大模型之Numpy_Pandas_按睡眠时间和压力等级统计睡眠质量.mp4
11_AI大模型之Numpy_Pandas_睡眠时间、压力等级、职业、性别统计睡眠质量.mp4
12_AI大模型之Numpy_Pandas_Pandas日期类型.mp4
13_AI大模型之Numpy_Pandas_时间序列.mp4
14_AI大模型之Numpy_Pandas_Matplotlib绘图.mp4
代码.exe
尚硅谷大模型技术之numpy与pandas1.0.docx
每日一考.md
05
00_AI大模型之Numpy_Pandas_内容回顾.mp4
01_AI大模型之Numpy_Pandas_面向对象的方式显示正余弦.mp4
02_AI大模型之Numpy_Pandas_Matplotlib直方图以及散点图.mp4
03_AI大模型之Numpy_Pandas_Pandas的Plot的绘图展示.mp4
04_AI大模型之Numpy_Pandas_Seaborn可视化.mp4
05_AI大模型之Numpy_Pandas_房价评估项目介绍.mp4
06_AI大模型之Numpy_Pandas_数据的导入以及清洗.mp4
07_AI大模型之Numpy_Pandas_添加新的特征(1).mp4
07_AI大模型之Numpy_Pandas_添加新的特征.mp4
08_AI大模型之Numpy_Pandas_描述性和相关性统计.mp4
09_AI大模型之Numpy_Pandas_分组聚合统计以及可视化.mp4
10_AI大模型之Numpy_Pandas_总结.mp4
代码.exe
每日一考.md
06_机器学习核心
1.笔记
尚硅谷大模型技术之数学基础1.0.0.docx
尚硅谷大模型技术之机器学习1.0.1.docx
2.资料
data
advertising.csv
heart_disease.csv
train.csv
3.代码
4.视频
01
1_课程整体介绍.wmv
2_数学基础_导数.wmv
3_练习_函数和导数.wmv
4_偏导数和梯度.wmv
5_向量运算.wmv
6_矩阵运算.wmv
7_矩阵求导.wmv
8_梯度矩阵.wmv
9_练习_计算梯度.wmv
10_概率和概率分布.wmv
11_练习_生成随机数.wmv
12_贝叶斯定理.wmv
13_极大似然估计.wmv
14_机器学习概述.wmv
15_机器学习发展历史.wmv
02
1_机器学习应用领域.wmv
2_机器学习基本术语.wmv
3_机器学习方法分类.wmv
4_机器学习建模流程.wmv
5_特征工程的内容.wmv
6_特征工程方法_低方差过滤法.wmv
7_特征工程方法_皮尔逊相关系数法.wmv
8_特征工程方法_斯皮尔曼相关系数法.wmv
9_特征工程方法_PCA.wmv
10_PCA补充说明.wmv
11_PCA补充说明2.wmv
03
1_损失函数.wmv
2_经验误差和泛化误差.wmv
3_欠拟合和过拟合.wmv
4_拟合案例_欠拟合.wmv
5_拟合案例_恰好拟合和过拟合.wmv
6_拟合案例_问题解答.wmv
7_拟合案例_问题解答补充.wmv
8_正则化.wmv
9_正则化_问题解答.wmv
10_正则化_案例.wmv
11_交叉验证.wmv
12_交叉验证_补充说明.wmv
13_模型求解算法_解析法.wmv
14_交叉验证_补充说明2.wmv
ch02_base_Day03.zip
05
1_机器学习基本理论复习总结.wmv
2_ROC_补充说明.wmv
3_KNN_原理介绍.wmv
4_KNN_API示例_分类.wmv
5_KNN_API示例_回归.wmv
6_补充说明_距离计算和权重.wmv
7_KNN_距离度量方法.wmv
8_归一化.wmv
9_标准化.wmv
10_心脏病案例_数据集说明和加载.wmv
11_心脏病案例_数据集划分.wmv
12_心脏病案例_特征工程.wmv
13_心脏病案例_模型训练和评估.wmv
14_心脏病案例_模型保存加载和预测.wmv
15_心脏病案例_网格搜索和交叉验证.wmv
ml_tutorial_Day05.zip
06
1_复习回顾_KNN.wmv
2_补充说明_网格搜索和交叉验证.wmv
3_线性回归_原理和应用.wmv
4_线性回归_API应用示例.wmv
5_线性回归_损失函数.wmv
6_线性回归_最小二乘法求解一元线性回归.wmv
7_线性回归_正规方程法求解.wmv
8_线性回归_API_截距参数.wmv
9_线性回归_梯度下降法.wmv
10_线性回归_梯度下降法主要问题.wmv
11_线性回归_梯度下降法API调用.wmv
12_线性回归案例_广告效果预测.wmv
ml_tutorial_Day06.exe
07
1_复习回顾_线性回归.wmv
2_问题解答_梯度下降tol参数.wmv
3_逻辑回归_基本概念和原理.wmv
4_逻辑回归_函数表达式补充说明.wmv
5_逻辑回归_应用场景.wmv
6_逻辑回归_损失函数.wmv
7_逻辑回归_损失函数的梯度.wmv
8_逻辑回归_API参数介绍.wmv
9_逻辑回归_应用案例_心脏病检测.wmv
10_逻辑回归_多分类任务.wmv
11_逻辑回归案例_手写数字识别.wmv
12_感知机_基本介绍.wmv
13_感知机_逻辑门电路.wmv
14_感知机_简单实现与门.wmv
15_感知机_实现逻辑门电路.wmv
16_感知机_感知机的局限.wmv
17_感知机_多层感知机实现异或门.wmv
ml_tutorial_Day07.zip
08
1_复习回顾_逻辑回归和感知机.wmv
2_朴素贝叶斯_基本原理.wmv
3_朴素贝叶斯_贝叶斯估计.wmv
4_决策树_基本原理和工作过程.wmv
5_决策树_信息熵和条件熵.wmv
6_决策树_信息增益.wmv
7_决策树_信息增益率和基尼系数.wmv
8_决策树_回归树.wmv
9_决策树_剪枝.wmv
10_支持向量机.wmv
11_集成学习_基本介绍.wmv
12_集成学习_AdaBoost.wmv
13_集成学习_随机森林.wmv
14_聚类_原理简介和聚类算法.wmv
ml_tutorial_Day08.zip
09
1_复习回顾_其它监督学习和聚类算法.wmv
2_聚类_KMeans代码示例.wmv
3_聚类_评价指标.wmv
4_降维_奇异值分解.wmv
5_降维_主成分分析.wmv
6_机器学习总体复习.wmv
ml_tutorial.zip
机器学习测试题（答案版）.docx
Day04
1_机器学习流程总结.wmv
2_梯度下降法.wmv
3_梯度下降法分类.wmv
4_梯度下降法具体步骤.wmv
5_梯度下降法案例_求函数最小值.wmv
6_梯度下降法案例_求函数目标值的位置.wmv
7_学习率的调整.wmv
8_梯度下降法应用.wmv
9_牛顿法和逆牛顿法.wmv
10_回归模型评价指标.wmv
11_分类模型评价指标_混淆矩阵.wmv
12_分类模型评价指标_精确率和召回率.wmv
13_分类模型评价指标_f1和分类报告.wmv
14_分类模型评价指标_ROC和AUC.wmv
ml_tutorial_Day04.zip
07_深度学习核心
1.笔记
尚硅谷大模型技术之深度学习1.0.0 .docx
2.资料
data
duck.jpg
fashion-mnist_test.csv
fashion-mnist_train.csv
house_prices.csv
house_prices_cols.txt
poems.txt
3.代码
4.视频
01
1_深度学习课程简介.wmv
2_深度学习_概述.wmv
3_神经网络_基本概念和构成.wmv
4_神经网络_从感知机到激活函数.wmv
5_神经网络_激活函数（一）.wmv
6_神经网络_激活函数（二）.wmv
7_神经网络_激活函数（三）.wmv
8_神经网络_三层网络结构和信号传递.wmv
9_神经网络_三层网络的代码实现.wmv
10_问题解答.wmv
dl_tutorial_Day01.zip
02
1_复习回顾_神经网络基础.wmv
2_神经网络_应用案例_整体介绍.wmv
3_神经网络_应用案例_代码实现.wmv
4_神经网络_应用案例_批量处理改进.wmv
5_神经网络和机器学习的联系和区别.wmv
6_神经网络的学习_损失函数.wmv
7_问题解答_交叉熵损失函数实现.wmv
8_导数和数值微分.wmv
9_导数和数值微分_应用案例.wmv
10_偏导数和梯度.wmv
11_数值微分计算梯度矩阵.wmv
12_神经网络的梯度计算.wmv
13_问题解答.wmv
dl_tutorial_Day02.zip
03
1_复习总结_损失函数和梯度.wmv
2_问题解答_损失函数代码实现.wmv
3_梯度下降法_原理和代码实现.wmv
4_随机梯度下降法.wmv
5_模型训练相关概念.wmv
6_SGD应用案例（一）_实现两层网络类.wmv
7_SGD应用案例（二）_计算梯度.wmv
8_SGD应用案例（三）_两层网络类总结.wmv
9_SGD应用案例（四）_SGD训练模型.wmv
10_问题解答_SGD训练模型.wmv
11_反向传播_计算图和BP基本原理.wmv
12_反向传播_链式法则和加法乘法规则.wmv
dl_tutorial_Day03.zip
04
1_复习回顾_SGD和反向传播.wmv
2_激活层反向传播_ReLU.wmv
3_问题解答_ReLU反向传播.wmv
4_问题解答2_ReLU反向传播.wmv
5_激活层反向传播_Sigmoid.wmv
6_问题解答_Sigmoid反向传播.wmv
7_Affine反向传播_原理推导.wmv
8_Affine反向传播_代码实现.wmv
9_输出层反向传播_Softmax+Loss.wmv
10_问题解答_Softmax+Loss.wmv
11_输出层反向传播_代码实现.wmv
12_反向传播案例_两层网络代码实现.wmv
13_反向传播案例_SGD代码实现和测试.wmv
14_问题解答_输出层反向传播.wmv
dl_tutorial_Day04.zip
06
1_复习回顾_学习方法优化.wmv
2_参数初始化_常数初始化.wmv
3_参数初始化_Xavier初始化和He初始化.wmv
4_正则化_批量标准化.wmv
5_正则化_权值衰减和随机失活.wmv
6_PyTorch_安装验证.wmv
7_PyTorch_张量的创建_基本创建方法.wmv
8_PyTorch_张量的创建_指定Tensor类型.wmv
9_问题解答_Tensor创建方法对比.wmv
10_PyTorch_张量的创建_指定区间.wmv
11_PyTorch_张量的创建_指定填充数值.wmv
12_PyTorch_张量的创建_随机创建.wmv
13_PyTorch_张量转换_元素类型转换.wmv
14_PyTorch_张量转换_张量和ndarray转换.wmv
15_PyTorch_张量数值计算_基本运算.wmv
16_PyTorch_张量数值计算_矩阵乘法运算.wmv
dl_tutorial.zip
07
1_复习回顾.wmv
2_节省内存操作.wmv
3_问题解答_节省内存操作.wmv
4_张量统计计算_维度介绍和sum求和.wmv
5_张量统计计算_其它统计聚合函数.wmv
6_张量统计计算_unique去重.wmv
7_张量统计计算_sort排序.wmv
8_张量索引_简单索引和范围索引.wmv
9_张量索引_列表索引和布尔索引.wmv
10_张量交换维度.wmv
11_张量调整形状.wmv
12_张量增加和删除维度.wmv
13_张量拼接和堆叠.wmv
14_自动微分模块_简单网络中的梯度计算.wmv
15_自动微分模块_叶子节点和非叶子结点.wmv
dl_tutorial_Day07.zip
08
1_复习回顾.wmv
2_自动微分模块_detach.wmv
3_自动微分模块_detach对梯度计算的影响测试.wmv
4_线性回归案例.wmv
5_问题解答_matplotlib不兼容.wmv
6_PyTorch深度学习_激活函数_Sigmoid.wmv
7_PyTorch深度学习_data和detach方法对比.wmv
8_PyTorch深度学习_其它激活函数.wmv
9_PyTorch深度学习_参数初始化.wmv
10_PyTorch深度学习_Dropout.wmv
11_PyTorch深度学习_搭建简单神经网络.wmv
dl_tutorial_Day08.zip
09
1_复习回顾.wmv
2_问题解答_Module的前向传播和特殊方法.wmv
3_神经网络_查看模型结构和参数.wmv
4_神经网络_定义设备.wmv
5_神经网络_使用Sequential定义神经网络.wmv
6_问题解答_定义设备.wmv
7_损失函数_分类问题_交叉熵损失.wmv
8_问题解答_分类交叉熵损失函数.wmv
9_损失函数_回归问题损失函数.wmv
10_损失函数_综合应用示例.wmv
11_学习优化方法_动量法.wmv
12_学习优化方法_动量法手动实现.wmv
dl_tutorial_Day09.zip
10
1_复习回顾.wmv
2_问题解答_动量法代码优化.wmv
3_学习优化方法_学习率衰减_等间隔.wmv
4_学习优化方法_学习率衰减_指定间隔和指数衰减.wmv
5_学习优化方法_AdaGrad_调库实现.wmv
6_学习优化方法_AdaGrad_手动实现.wmv
7_学习优化方法_RMSProp.wmv
8_学习优化方法_Adam.wmv
9_综合应用案例_房价预测_数据介绍和整体架构.wmv
10_综合应用案例_房价预测_构建数据集.wmv
11_问题解答_列转换.wmv
12_综合应用案例_房价预测_创建神经网络模型.wmv
13_综合应用案例_房价预测_定义损失函数.wmv
14_综合应用案例_房价预测_训练和测试模型.wmv
15_综合应用案例_房价预测_整体运行测试.wmv
16_问题解答_随机划分训练集和打印进度条.wmv
dl_tutorial_Day10.zip
11
1_复习回顾.wmv
2_复习总结_神经网络和深度学习基础.wmv
3_CNN_基本概念和整体结构.wmv
4_CNN_卷积运算数学原理.wmv
5_CNN_卷积层的卷积运算.wmv
6_CNN_填充和步幅.wmv
7_CNN_高维数据卷积运算.wmv
8_问题解答_偏置.wmv
9_CNN_卷积层API.wmv
10_问题解答_卷积层API代码.wmv
11_扩展_分组卷积和膨胀卷积.wmv
12_CNN_池化层.wmv
13_CNN_池化层API.wmv
dl_tutorial_Day11.zip
12
1_复习回顾.wmv
2_CNN的发展和变化.wmv
3_CNN应用案例_数据加载和预处理.wmv
4_CNN应用案例_创建神经网络模型.wmv
5_CNN应用案例_问题解答_模型各层输入输出形状.wmv
6_CNN应用案例_模型训练和测试.wmv
7_CNN应用案例_问题解答_训练误差的统计.wmv
8_CNN应用案例_代码测试.wmv
9_RNN_自然语言处理概述.wmv
10_RNN_自然语言处理应用.wmv
11_词嵌入_基本概念和原理.wmv
12_词嵌入层_深入理解.wmv
13_词嵌入层_API.wmv
dl_tutorial_Day12.zip
13
1_复习回顾.wmv
2_RNN的发展历史.wmv
3_RNN基本原理和数学表达.wmv
4_RNN_API调用.wmv
5_问题解答_隐状态的维度.wmv
6_RNN案例_古诗生成_数据预处理.wmv
7_RNN案例_古诗生成_构建训练数据集.wmv
8_RNN案例_古诗生成_创建模型.wmv
9_RNN案例_古诗生成_模型训练.wmv
9_问题说明.wmv
10_RNN案例_古诗生成_生成测试.wmv
dl_tutorial.zip
Day05
1_复习回顾_反向传播.wmv
2_问题解答_代码赋值.wmv
3_深度学习_基本概念.wmv
4_梯度消失和梯度爆炸.wmv
5_SGD的问题和代码实现.wmv
6_动量法.wmv
7_学习率衰减.wmv
8_AdaGrad.wmv
9_RMSProp.wmv
10_Adam.wmv
11_更新参数优化方法比较.wmv
12_PyTorch简介和安装说明.wmv
dl_tutorial_Day05.zip
08_大模型项目之智图寻宝
1.笔记
尚硅谷大模型技术之智图寻宝-v1.0.1.docx
2.资料
Apple.jpg
dataset.zip
fashion-labels.csv
logo
logo.jpg
pictures.zip
神经网络架构图
去噪器.png
去噪器.svg
相似度检索-编码器.png
相似度检索-编码器.svg
相似度检索-编解码器.png
相似度检索-编解码器.svg
相似度检索-解码器.png
相似度检索-解码器.svg
相似度检索编解码器架构配置.png
聚类架构.png
聚类架构.svg
聚类架构配置.png
苹果-编码器.png
苹果-编码器.svg
苹果-自编码器.png
苹果-自编码器.svg
苹果-解码器.png
苹果-解码器.svg
3.代码
4.视频
01
1_智图寻宝项目_整体介绍.wmv
2_智图寻宝项目_项目架构.wmv
3_智图寻宝项目_环境准备.wmv
4_智图寻宝项目_公共模块.wmv
5_问题解答_benchmark.wmv
6_智图寻宝项目_自编码器.wmv
7_智图寻宝项目_案例_编码器结构.wmv
8_智图寻宝项目_案例_解码器结构.wmv
9_智图寻宝项目_案例_加载图片.wmv
10_智图寻宝项目_案例_创建模型.wmv
11_智图寻宝项目_案例_训练和重构图像.wmv
image_processing_Day01.zip
02
1_复习回顾.wmv
2_问题解答_引入噪声.wmv
3_智图寻宝项目_去噪模块_架构分析.wmv
4_问题解答_池化形状变化.wmv
5_智图寻宝项目_去噪模块_自定义数据集类.wmv
6_问题解答_图片通道数和加载方式.wmv
7_智图寻宝项目_去噪模块_数据集创建和加载.wmv
8_智图寻宝项目_去噪模块_模型创建.wmv
9_问题解答_通用池化层.wmv
10_智图寻宝项目_去噪模块_模型训练.wmv
11_智图寻宝项目_去噪模块_模型测试验证.wmv
12_智图寻宝项目_去噪模块实现_代码整体结构.wmv
image_processing_Day02.zip
03
1_扩展_转置卷积.wmv
2_智图寻宝项目_去噪模块实现_配置文件.wmv
3_智图寻宝项目_去噪模块实现_定义数据集.wmv
4_智图寻宝项目_去噪模块实现_数据集测试.wmv
5_智图寻宝项目_去噪模块实现_模型定义.wmv
6_智图寻宝项目_去噪模块实现_训练测试引擎.wmv
7_智图寻宝项目_去噪模块实现_训练模型.wmv
8_智图寻宝项目_去噪模块实现_测试模型效果.wmv
9_智图寻宝项目_去噪模块实现_测试结果说明.wmv
10_智图寻宝项目_分类模块_架构说明.wmv
11_智图寻宝项目_分类模块_创建数据集.wmv
12_智图寻宝项目_分类模块_创建模型.wmv
image_processing_Day03.zip
04
1_复习回顾.wmv
2_问题解答_模型架构设计.wmv
3_智图寻宝项目_分类模块_模型定义扩展.wmv
4_智图寻宝项目_分类模块_训练模型.wmv
5_智图寻宝项目_分类模块_模型测试和评估.wmv
6_智图寻宝项目_分类模块实现_配置文件.wmv
7_智图寻宝项目_分类模块实现_创建数据集.wmv
8_智图寻宝项目_分类模块实现_定义模型.wmv
9_智图寻宝项目_分类模块实现_模型训练和评估.wmv
10_智图寻宝项目_分类模块实现_训练和评估结果分析.wmv
11_智图寻宝项目_相似检索模块_实现思路和模型架构.wmv
12_智图寻宝项目_相似检索模块_配置文件.wmv
13_智图寻宝项目_相似检索模块_定义数据集.wmv
14_智图寻宝项目_相似检索模块_定义模型.wmv
15_智图寻宝项目_相似检索模块_引擎实现.wmv
16_智图寻宝项目_相似检索模块_模型训练.wmv
17_智图寻宝项目_相似检索模块_训练结果分析.wmv
image_processing_Day04.zip
05
1_复习回顾.wmv
2_作业讲解_模型的Sequential表达.wmv
3_问题解答_DataLoader.wmv
4_智图寻宝项目_web模块和综合测试.wmv
5_智图寻宝项目_web模块代码解析.wmv
6_智图寻宝项目_面试串讲_整体介绍和对比损失.wmv
7_智图寻宝项目_面试串讲_去噪模块和椒盐噪声.wmv
8_智图寻宝项目_面试串讲_感知损失.wmv
9_智图寻宝项目_面试串讲_模型训练和优化.wmv
image_processing.zip
09_NLP核心
1.笔记
尚硅谷大模型技术之NLP1.0.2.docx
2.资料
1.词向量
sgns.weibo.word
sgns.weibo.word
2.数据集
1.评论数据集
online_shopping_10_cats.csv
2.对话数据集
synthesized_.jsonl
3.中英短句数据集
cmn.txt
3.预训练模型
bert-base-chinese
.cache
huggingface
.gitignore
download
.gitattributes.metadata
README.md.metadata
config.json.metadata
flax_model.msgpack.metadata
model.safetensors.metadata
pytorch_model.bin.metadata
tf_model.h5.metadata
tokenizer.json.metadata
tokenizer_config.json.metadata
vocab.txt.metadata
.gitattributes
README.md
config.json
flax_model.msgpack
model.safetensors
pytorch_model.bin
tf_model.h5
tokenizer.json
tokenizer_config.json
vocab.txt
3.代码
4.视频
01
01-大模型-NLP-课程介绍.mp4
02-大模型-NLP-导论-常见任务.mp4
03-大模型-NLP-导论-技术演进历史.mp4
04-大模型-NLP-文本表示-概述.mp4
05-大模型-NLP-文本表示-英文分词.mp4
06-大模型-NLP-文本表示-中文分词.mp4
07-大模型-NLP-文本表示-分词工具概述.mp4
08-大模型-NLP-文本表示-分词工具-jieba-分词模式.mp4
09-大模型-NLP-文本表示-分词工具-jieba-自定义词典.mp4
10-大模型-NLP-文本表示-词表示-概述&one-hot&语义化词向量概述.mp4
11-大模型-NLP-文本表示-词表示-Word2Vec-概述.mp4
12-大模型-NLP-文本表示-词表示-Word2Vec-数据集说明.mp4
13-大模型-NLP-文本表示-词表示-Word2Vec-模型结构&训练逻辑.mp4
14-大模型-NLP-文本表示-词表示-Word2Vec-gensim概述.mp4
15-大模型-NLP-文本表示-词表示-Word2Vec-公开词向量介绍.mp4
16-大模型-NLP-文本表示-词表示-Word2Vec-加载公开词向量.mp4
17-大模型-NLP-文本表示-词表示-Word2Vec-自行训练词向量-说明.mp4
18-大模型-NLP-文本表示-词表示-Word2Vec-自行训练词向量-实操.mp4
19-大模型-NLP-文本表示-词表示-初始化Embedding-说明.mp4
20-大模型-NLP-小总结.mp4
word_represent
01-tokenizer.ipynb
02-word2vec.ipynb
data
online_shopping_10_cats.csv
sgns.weibo.word.bz2
user_dict.txt
word2vec.txt
02
01-大模型-NLP-文本表示-词表示-语义化词向量-Word2vec-应用-概述.mp4
02
input-method
.idea
.gitignore
input-method.iml
inspectionProfiles
Project_Default.xml
profiles_settings.xml
misc.xml
modules.xml
workspace.xml
data
processed
indexed_test.jsonl
indexed_train.jsonl
raw
synthesized_.jsonl
logs
main.py
models
pd_json.py
src
__pycache__
config.cpython-312.pyc
config.py
process.py
word_represent
01-tokenizer.ipynb
02-word2vec.ipynb
.idea
.gitignore
inspectionProfiles
Project_Default.xml
profiles_settings.xml
misc.xml
modules.xml
word_represent.iml
workspace.xml
data
online_shopping_10_cats.csv
sgns.weibo.word.bz2
user_dict.txt
word2vec.txt
02-大模型-NLP-文本表示-词表示-语义化词向量-Word2vec-应用-编码.mp4
03-大模型-NLP-文本表示-词表示-上下文相关词向量-介绍.mp4
04-大模型-NLP-传统序列模型-RNN-概述.mp4
05-大模型-NLP-传统序列模型-RNN-基础结构.mp4
06-大模型-NLP-传统序列模型-RNN-数学公式.mp4
07-大模型-NLP-传统序列模型-RNN-多层结构.mp4
08-大模型-NLP-传统序列模型-RNN-双向结构.mp4
09-大模型-NLP-传统序列模型-RNN-多层&双向结构.mp4
10-大模型-NLP-传统序列模型-RNN-API使用-概述.mp4
11-大模型-NLP-传统序列模型-RNN-API使用-构造参数.mp4
12-大模型-NLP-传统序列模型-RNN-API使用-输入输出-概述.mp4
13-大模型-NLP-传统序列模型-RNN-API使用-输入输出-单层单向.mp4
14-大模型-NLP-传统序列模型-RNN-API使用-输入输出-多层单向.mp4
15-大模型-NLP-传统序列模型-RNN-API使用-输入输出-单层双向&多层双向.mp4
16-大模型-NLP-传统序列模型-RNN-API练习.mp4
17-大模型-NLP-传统序列模型-RNN-案例实操-需求说明.mp4
18-大模型-NLP-传统序列模型-RNN-案例实操-思路分析-数据集.mp4
19-大模型-NLP-传统序列模型-RNN-案例实操-思路分析-模型设计.mp4
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modules.xml
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tokenizer.cpython-312.pyc
config.py
dataset.py
evaluate.py
main.py
model.py
predict.py
process.py
tokenizer.py
train.py
test
test.ipynb
test.py
test_bleu.py
translation-seq2seq
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.gitignore
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Project_Default.xml
profiles_settings.xml
misc.xml
modules.xml
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workspace.xml
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cmn.txt
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decoder.pt
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tokenizer.cpython-312.pyc
config.py
dataset.py
evaluate.py
main.py
model.py
predict.py
process.py
tokenizer.py
train.py
test
test_bleu.py
translation-transformer
.idea
.gitignore
inspectionProfiles
Project_Default.xml
profiles_settings.xml
misc.xml
modules.xml
translation-transformer.iml
workspace.xml
data
processed
en_vocab.txt
indexed_test.jsonl
indexed_train.jsonl
zh_vocab.txt
raw
cmn.txt
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config.py
dataset.py
evaluate.py
main.py
model.py
predict.py
process.py
tokenizer.py
train.py
word_represent
01-tokenizer.ipynb
02-word2vec.ipynb
.idea
.gitignore
inspectionProfiles
Project_Default.xml
profiles_settings.xml
misc.xml
modules.xml
word_represent.iml
workspace.xml
data
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user_dict.txt
word2vec.txt
11-大模型-NLP-预训练模型-案例-预处理脚本.mp4
12-大模型-NLP-预训练模型-案例-Dataloader集成.mp4
13-大模型-NLP-预训练模型-案例-模型定义.mp4
14-大模型-NLP-预训练模型-案例-训练.mp4
15-大模型-NLP-预训练模型-案例-预测和评估.mp4
10_大模型项目之智能商品发布
1.笔记
尚硅谷大模型技术之智能商品发布1.0.0.docx
4.视频
01
01
Couplet-Transformer
data
.DS_Store
processed
couplet.jsonl
vocab.txt
raw
in.txt
out.txt
models
model.pt
src
.DS_Store
__pycache__
config.cpython-312.pyc
dataset.cpython-312.pyc
model.cpython-312.pyc
process.cpython-312.pyc
tokenizer.cpython-312.pyc
config.py
dataset.py
main.py
model.py
predict.py
process.py
tokenizer.py
train.py
product-classify-bert
data
processed
test
data-00000-of-00001.arrow
dataset_info.json
state.json
train
data-00000-of-00001.arrow
dataset_info.json
state.json
valid
data-00000-of-00001.arrow
dataset_info.json
state.json
raw
test.txt
train.txt
valid.txt
logs
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2025-07-02_15-43-41
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models
best.pt
pretrained
bert-base-chinese
.cache
huggingface
.gitignore
download
.gitattributes.metadata
README.md.metadata
config.json.metadata
flax_model.msgpack.metadata
model.safetensors.metadata
pytorch_model.bin.metadata
tf_model.h5.metadata
tokenizer.json.metadata
tokenizer_config.json.metadata
vocab.txt.metadata
.gitattributes
README.md
config.json
model.safetensors
tokenizer.json
tokenizer_config.json
vocab.txt
src
configuration
__init__.py
__pycache__
__init__.cpython-312.pyc
config.cpython-312.pyc
config.py
main.py
model
__init__.py
__pycache__
__init__.cpython-312.pyc
bert_classifier.cpython-312.pyc
bert_classifier.py
preprocess
__init__.py
__pycache__
__init__.cpython-312.pyc
dataset.cpython-312.pyc
process.cpython-312.pyc
dataset.py
process.py
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__init__.py
__pycache__
__init__.cpython-312.pyc
predict.cpython-312.pyc
train.cpython-312.pyc
predict.py
train.py
web
__init__.py
01-大模型-NLP-对联案例-小结.mp4
02-大模型-NLP-智能商品发布-方案分析.mp4
03-大模型-NLP-智能商品发布-方案总结.mp4
04-大模型-NLP-智能商品发布-开发环境说明.mp4
05-大模型-NLP-智能商品发布-创建项目.mp4
06-大模型-NLP-智能商品发布-数据预处理-加载数据&tokenize.mp4
07-大模型-NLP-import路径说明.mp4
08-大模型-NLP-智能商品发布-数据预处理-统计标题长度.mp4
09-大模型-NLP-import-路径说明-总结.mp4
10-大模型-NLP-智能商品发布-数据预处理-标签处理&保存数据集.mp4
11-大模型-NLP-智能商品发布-dataset&Dataloader.mp4
12-大模型-NLP-智能商品发布-枚举类型简要说明.mp4
13-大模型-NLP-智能商品发布-模型定义.mp4
14-大模型-NLP-智能商品发布-模型训练.mp4
15-大模型-NLP-智能商品发布-预测脚本.mp4
PyCharm import路径说明.md
层级标签预测任务说明.drawio
_02
01-大模型-NLP-智能商品发布-多分类任务评估指标说明.mp4
02-大模型-NLP-智能商品发布-评估脚本.mp4
03-大模型-NLP-智能商品发布-训练优化-早停策略-概述.mp4
04-大模型-NLP-智能商品发布-训练优化-早停策略-核心逻辑.mp4
05-大模型-NLP-智能商品发布-训练优化-早停策略-改造train_one_epoch.mp4
06-大模型-NLP-智能商品发布-训练优化-混合精度训练-概述.mp4
07-大模型-NLP-智能商品发布-训练优化-混合精度训练-官网案例.mp4
08-大模型-NLP-智能商品发布-训练优化-混合精度训练-编码.mp4
09-大模型-NLP-智能商品发布-训练优化-检查点机制-说明.mp4
10-大模型-NLP-智能商品发布-训练优化-检查点机制-编码.mp4
11-大模型-NLP-智能商品发布-部署与应用-fastapi-概述.mp4
12-大模型-NLP-智能商品发布-部署与应用-fastapi-前端知识扫盲.mp4
13-大模型-NLP-智能商品发布-部署与应用-fastapi-工作原理小结.mp4
14-大模型-NLP-智能商品发布-部署与应用-fastapi-交互式API文档.mp4
15-大模型-NLP-智能商品发布-部署与应用-fastapi-PUT请求.mp4
16-大模型-NLP-智能商品发布-部署与应用-fastapi-使用逻辑小结.mp4
17-大模型-NLP-智能商品发布-部署与应用-预测接口核心逻辑.mp4
18-大模型-NLP-智能商品发布-部署与应用-错误处理.mp4
19-大模型-NLP-智能商品发布-部署与应用-web模块规范化.mp4
20-大模型-NLP-智能商品发布-入口脚本编写-argparse用法说明.mp4
21-大模型-NLP-智能商品发布-入口脚本编写-完整逻辑.mp4
_02
product-classify-bert
.idea
.gitignore
deployment.xml
inspectionProfiles
Project_Default.xml
profiles_settings.xml
misc.xml
modules.xml
product-classify-bert.iml
workspace.xml
data
processed
test
data-00000-of-00001.arrow
dataset_info.json
state.json
train
data-00000-of-00001.arrow
dataset_info.json
state.json
valid
data-00000-of-00001.arrow
dataset_info.json
state.json
raw
test.txt
train.txt
valid.txt
logs
2025-07-02_15-43-14
events.out.tfevents.1751442194.LAPTOP-AII3AT3S.56100.0
2025-07-02_15-43-41
events.out.tfevents.1751442221.LAPTOP-AII3AT3S.51056.0
2025-07-04_10-31-48
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2025-07-04_19-03-09
events.out.tfevents.1751626989.LAPTOP-AII3AT3S.31208.0
models
best.pt
checkpoint.pt
pretrained
bert-base-chinese
.cache
huggingface
.gitignore
download
.gitattributes.metadata
README.md.metadata
config.json.metadata
flax_model.msgpack.metadata
model.safetensors.metadata
pytorch_model.bin.metadata
tf_model.h5.metadata
tokenizer.json.metadata
tokenizer_config.json.metadata
vocab.txt.metadata
.gitattributes
README.md
config.json
flax_model.msgpack
model.safetensors
pytorch_model.bin
tf_model.h5
tokenizer.json
tokenizer_config.json
vocab.txt
src
__pycache__
configuration
__init__.py
__pycache__
__init__.cpython-312.pyc
config.cpython-312.pyc
config.py
main.py
model
__init__.py
__pycache__
__init__.cpython-312.pyc
bert_classifier.cpython-312.pyc
bert_classifier.py
preprocess
__init__.py
__pycache__
__init__.cpython-312.pyc
dataset.cpython-312.pyc
process.cpython-312.pyc
dataset.py
process.py
runner
__init__.py
__pycache__
__init__.cpython-312.pyc
evaluate.cpython-312.pyc
predict.cpython-312.pyc
train.cpython-312.pyc
evaluate.py
predict.py
train.py
web
__init__.py
__pycache__
__init__.cpython-312.pyc
app.cpython-312.pyc
predict_router.cpython-312.pyc
schemas.cpython-312.pyc
service.cpython-312.pyc
app.py
predict_router.py
schemas.py
service.py
test
__init__.py
__pycache__
__init__.cpython-312.pyc
test_fastapi.cpython-312.pyc
test_m.cpython-312.pyc
test_amp.py
test_fastapi.py
test_float.py
test_m.py
11_大模型项目实战之地址对齐
1.笔记
尚硅谷大模型项目实战之地址对齐1.0.docx
2.资料
address-alignment
data
raw
data.txt
region.sql
pretrained
bert-base-chinese
.gitattributes
README.md
config.json
model.safetensors
tokenizer.json
tokenizer_config.json
vocab.txt
templates
index.html
marked.min.js
purify.min.js
尚硅谷大模型项目实战之地址对齐.docx
3.代码
address-alignment
address_alignment.py
app.py
config.py
data_prepare.py
desc
main.py
models_def.py
preprocess.py
train.py
4.视频
12_大模型项目实战之智选新闻
1.笔记
尚硅谷大模型项目实战之智选新闻1.0.docx
2.资料
ai-news
data
news.csv
pretrained
bart-base-chinese
.gitattributes
README.md
config.json
model.safetensors
special_tokens_map.json
tokenizer_config.json
vocab.txt
bert-base-chinese
.gitattributes
README.md
config.json
model.safetensors
tokenizer.json
tokenizer_config.json
vocab.txt
rouge
rouge.json
rouge.py
templates
index.html
尚硅谷大模型项目实战之智选新闻.docx
3.代码
ai-news-code
app.py
common.py
desc
main.py
models_def.py
preprocess.py
train.py
4.视频
13_大模型项目之智荐图谱
1.笔记
尚硅谷大模型技术之电商图谱1.0.0.docx
2.资料
1.数据集
images
36
1.jpg
2.jpg
3.jpg
4.jpg
5.jpg
6.jpg
7.jpg
8.jpg
9.jpg
10.jpg
11.jpg
12.jpg
13.jpg
14.jpg
15.jpg
16.jpg
17.jpg
37
1.jpg
2.jpg
3.jpg
4.jpg
38
1.jpg
2.jpg
3.jpg
39
1.jpg
2.jpg
3.jpg
4.jpg
5.jpg
6.jpg
40
1.jpg
2.jpg
3.jpg
4.jpg
5.jpg
6.jpg
41
1.jpg
2.jpg
3.jpg
4.jpg
42
1.jpg
2.jpg
3.jpg
4.jpg
43
1.jpg
2.jpg
3.jpg
4.jpg
5.jpg
intent_classify
data.csv
spell_check
data.txt
uie
data.txt
doccano.jsonl
label_config.json
数据库
gmall.sql
2.预训练模型
bert-base-chinese
config.json
model.safetensors
tokenizer.json
tokenizer_config.json
vocab.txt
3.代码
4.视频
_01
01-项目实战-地址对齐-核心思路.mp4
02-项目实战-摘要-核心思路.mp4
03-项目实战-摘要-BeamSearch说明.mp4
04-大模型-NLP-电商图谱-项目-概述.mp4
05-大模型-NLP-电商图谱-项目-数据来源说明.mp4
06-大模型-NLP-电商图谱-项目-构建知识图谱-概述.mp4
07-大模型-NLP-电商图谱-项目-构建知识图谱-项目应用-概述.mp4
08-大模型-NLP-项目实战问题说明-ssh隧道.mp4
09-大模型-NLP-电商图谱-拼写纠错模型-概述.mp4
10-大模型-NLP-电商图谱-拼写纠错模型-项目准备.mp4
11-大模型-NLP-电商图谱-拼写纠错模型-数据预处理-上.mp4
12-大模型-NLP-电商图谱-拼写纠错模型-数据预处理-下.mp4
13-大模型-NLP-电商图谱-拼写纠错模型-模型&Trainer设计思路.mp4
14-大模型-NLP-电商图谱-拼写纠错模型-模型定义.mp4
15-大模型-NLP-电商图谱-拼写纠错模型-Trainer定义.mp4
16-大模型-NLP-电商图谱-拼写纠错模型-Trainer-train方法编写.mp4
17-大模型-NLP-电商图谱-拼写纠错模型-Trainer-train方法测试.mp4
_01
graph
.idea
.gitignore
deployment.xml
graph.iml
inspectionProfiles
Project_Default.xml
profiles_settings.xml
misc.xml
modules.xml
workspace.xml
checkpoint
spell_check_bert
best.pt
data
spell_check
processed
bert
dataset_dict.json
test
data-00000-of-00001.arrow
dataset_info.json
state.json
train
data-00000-of-00001.arrow
dataset_info.json
state.json
valid
data-00000-of-00001.arrow
dataset_info.json
state.json
t5
raw
data.txt
logs
pretrained
bert-base-chinese
config.json
model.safetensors
tokenizer.json
tokenizer_config.json
vocab.txt
src
configs
__init__.py
__pycache__
__init__.cpython-312.pyc
config.cpython-312.pyc
config.py
models
__init__.py
__pycache__
__init__.cpython-312.pyc
spell_check_bert.cpython-312.pyc
spell_check_bert.py
preprocess
__init__.py
process_spell_check.py
runner
Trainer.py
__init__.py
web
__init__.py
知识图谱项目.drawio
项目实战核心思路梳理.drawio
_02
01-大模型-NLP-电商图谱-拼写纠错模型-Trainer-train方法改造说明.mp4
02-大模型-NLP-电商图谱-拼写纠错模型-Trainer-改造step粒度.mp4
03-大模型-NLP-电商图谱-拼写纠错模型-Trainer-evaluate方法编写.mp4
04-大模型-NLP-电商图谱-拼写纠错模型-Trainer-evaluate方法-完善.mp4
05-大模型-NLP-电商图谱-拼写纠错模型-Trainer-compute_metrics要求.mp4
06-大模型-NLP-电商图谱-拼写纠错模型-Trainer-compute_metrics测试.mp4
07-大模型-NLP-电商图谱-拼写纠错模型-Trainer-早停.mp4
08-大模型-NLP-电商图谱-拼写纠错模型-Trainer-Checkpoint.mp4
09-大模型-NLP-电商图谱-拼写纠错模型-Trainer-混合精度训练.mp4
10-大模型-NLP-电商图谱-拼写纠错模型-云环境准备.mp4
11-大模型-NLP-电商图谱-拼写纠错模型-同步代码&下载模型.mp4
12-大模型-NLP-电商图谱-拼写纠错模型-开始训练.mp4
13-大模型-NLP-电商图谱-拼写纠错模型-推理逻辑.mp4
14-大模型-NLP-电商图谱-拼写纠错模型-Train-212行-纠错.mp4
15-大模型-NLP-电商图谱-拼写纠错模型-预测逻辑说明.mp4
_02
graph
.idea
.gitignore
deployment.xml
graph.iml
inspectionProfiles
Project_Default.xml
profiles_settings.xml
misc.xml
modules.xml
workspace.xml
checkpoint
spell_check_bert
best.pt
data
spell_check
processed
bert
dataset_dict.json
test
data-00000-of-00001.arrow
dataset_info.json
state.json
train
data-00000-of-00001.arrow
dataset_info.json
state.json
valid
data-00000-of-00001.arrow
dataset_info.json
state.json
t5
raw
data.txt
logs
pretrained
bert-base-chinese
config.json
model.safetensors
tokenizer.json
tokenizer_config.json
vocab.txt
src
configs
__init__.py
__pycache__
__init__.cpython-312.pyc
config.cpython-312.pyc
config.py
models
__init__.py
__pycache__
__init__.cpython-312.pyc
spell_check_bert.cpython-312.pyc
spell_check_bert.py
preprocess
__init__.py
process_spell_check.py
runner
Predictor.py
Trainer.py
__init__.py
web
__init__.py
_03
01-大模型-NLP-电商图谱项目-纠错模型-T5概述.mp4
02-大模型-NLP-电商图谱项目-纠错模型-Huggingface-查询文档说明.mp4
03-大模型-NLP-电商图谱项目-纠错模型-T5模型-熟悉思路.mp4
04-大模型-NLP-电商图谱项目-纠错模型-T5模型-模型下载.mp4
05-大模型-NLP-电商图谱项目-纠错模型-T5模型-数据预处理.mp4
06-大模型-NLP-电商图谱项目-纠错模型-T5模型-模型定义.mp4
07-大模型-NLP-电商图谱项目-纠错模型-T5模型-模型训练.mp4
08-大模型-NLP-电商图谱项目-纠错模型-T5模型-Trainer改造思路.mp4
09-大模型-NLP-电商图谱项目-纠错模型-T5模型-BeamSearch思路回顾.mp4
10-大模型-NLP-电商图谱项目-纠错模型-T5模型-generate-上.mp4
11-大模型-NLP-电商图谱项目-纠错模型-T5模型-generate-中.mp4
12-大模型-NLP-电商图谱项目-纠错模型-T5模型-generate-下.mp4
13-大模型-NLP-电商图谱项目-纠错模型-T5模型-generate-完结.mp4
Mengzi-T5分词器依赖.txt
_03
graph
.idea
.gitignore
deployment.xml
graph.iml
inspectionProfiles
Project_Default.xml
profiles_settings.xml
misc.xml
modules.xml
workspace.xml
checkpoint
spell_check_bert
best.pt
data
spell_check
processed
bert
dataset_dict.json
test
data-00000-of-00001.arrow
dataset_info.json
state.json
train
data-00000-of-00001.arrow
dataset_info.json
state.json
valid
data-00000-of-00001.arrow
dataset_info.json
state.json
t5
raw
data.txt
logs
pretrained
bert-base-chinese
config.json
model.safetensors
tokenizer.json
tokenizer_config.json
vocab.txt
src
configs
__init__.py
__pycache__
__init__.cpython-312.pyc
config.cpython-312.pyc
config.py
models
__init__.py
__pycache__
__init__.cpython-312.pyc
spell_check_bert.cpython-312.pyc
spell_check_bert.py
spell_check_t5.py
preprocess
__init__.py
process_spell_check.py
runner
Predictor.py
Trainer.py
__init__.py
scripts
__init__.py
train_spell_check_bert.py
train_spell_check_t5.py
test.py
web
__init__.py
best.pt
生成策略.drawio
_04
01-大模型-NLP-电商图谱-纠错模型-T5-seq2seqTrainer-完结.mp4
02-大模型-NLP-电商图谱-纠错模型-T5-评估环境准备.mp4
03-大模型-NLP-电商图谱-纠错模型-T5-评估代码编写.mp4
04-大模型-NLP-电商图谱-纠错模型-T5-预测代码编写.mp4
05-大模型-NLP-电商图谱-后续安排.mp4
06-大模型-NLP-电商图谱-实体关系抽取-UIE-概述.mp4
07-大模型-NLP-电商图谱-纠错模型-T5-评估结果说明.mp4
08-大模型-NLP-电商图谱-实体关系抽取模型-UIE-结构说明.mp4
09-大模型-NLP-电商图谱-实体关系抽取模型-UIE-入门案例.mp4
10-大模型-NLP-电商图谱-实体关系抽取模型-UIE-电商数据抽取-演示.mp4
11-大模型-NLP-电商图谱-实体关系抽取模型-UIE-微调-数据标注工具.mp4
12-大模型-NLP-电商图谱-实体关系抽取模型-UIE-微调-数据标注演示.mp4
13-大模型-NLP-电商图谱-实体关系抽取模型-UIE-微调-数据集处理.mp4
14-大模型-NLP-电商图谱-实体关系抽取模型-UIE-微调-训练.mp4
15-大模型-NLP-电商图谱-实体关系抽取模型-UIE-各种路径梳理.mp4
16-大模型-NLP-电商图谱-实体关系抽取模型-图数据库neo4j-概述.mp4
17-大模型-NLP-电商图谱-实体关系抽取模型-图数据库neo4j-安装-JDK.mp4
18-大模型-NLP-电商图谱-实体关系抽取模型-图数据库neo4j-安装-neo4j.mp4
19-大模型-NLP-电商图谱-实体关系抽取模型-UIE-模型预测&评估.mp4
20-大模型-NLP-电商图谱-实体关系抽取模型-图数据库neo4j-脚本执行策略说明.mp4
_04
graph
.idea
.gitignore
deployment.xml
graph.iml
inspectionProfiles
Project_Default.xml
profiles_settings.xml
misc.xml
modules.xml
workspace.xml
checkpoint
spell_check_bert
best.pt
spell_check_t5
best.pt
data
spell_check
processed
bert
dataset_dict.json
test
data-00000-of-00001.arrow
dataset_info.json
state.json
train
data-00000-of-00001.arrow
dataset_info.json
state.json
valid
data-00000-of-00001.arrow
dataset_info.json
state.json
t5_20250718_175209
raw
data.txt
uie
processed
dev.txt
sample_index.json
test.txt
train.txt
raw
doccano.jsonl
external_lib
uie_pytorch
.gitignore
LICENSE
README.md
convert.py
doccano.md
doccano.py
ernie.py
ernie_m.py
evaluate.py
export_model.py
finetune.py
labelstudio2doccano.py
model.py
requirements.txt
tokenizer.py
uie_predictor.py
utils.py
logs
pretrained
bert-base-chinese
config.json
model.safetensors
tokenizer.json
tokenizer_config.json
vocab.txt
mengzi-t5
config.json
model.safetensors
spiece.model
spiece.vocab
uie_base_pytorch
config.json
pytorch_model.bin
special_tokens_map.json
tokenizer_config.json
vocab.txt
src
configs
__init__.py
__pycache__
__init__.cpython-312.pyc
config.cpython-312.pyc
config.py
models
__init__.py
__pycache__
__init__.cpython-312.pyc
spell_check_bert.cpython-312.pyc
spell_check_t5.cpython-312.pyc
spell_check_bert.py
spell_check_t5.py
preprocess
__init__.py
process_spell_check.py
runner
Predictor.py
Trainer.py
__init__.py
scripts
__init__.py
train_spell_check_bert.py
train_spell_check_t5.py
train_uie.py
web
__init__.py
_05
01-大模型-NLP-电商图谱项目-neo4j-Cypher-概述.mp4
02-大模型-NLP-电商图谱项目-neo4j-数据模型.mp4
03-大模型-NLP-电商图谱项目-neo4j-写入节点&查询节点.mp4
04-大模型-NLP-电商图谱项目-neo4j-写入关系&查询关系.mp4
05-大模型-NLP-电商图谱项目-neo4j-写入路径&查询路径.mp4
06-大模型-NLP-电商图谱项目-neo4j-修改数据.mp4
07-大模型-NLP-电商图谱项目-neo4j-删除数据.mp4
08-大模型-NLP-电商图谱项目-neo4j-MERGE数据.mp4
09-大模型-NLP-电商图谱项目-neo4j-MERGE操作-更新.mp4
10-大模型-NLP-电商图谱项目-neo4j-数据类型.mp4
11-大模型-NLP-电商图谱项目-neo4j-函数说明.mp4
12-大模型-NLP-电商图谱项目-neo4j-高级查询-数据准备.mp4
13-大模型-NLP-电商图谱项目-neo4j-高级查询-过滤.mp4
14-大模型-NLP-电商图谱项目-neo4j-高级查询-排序&分页.mp4
15-大模型-NLP-电商图谱项目-neo4j-高级查询-聚合.mp4
16-大模型-NLP-电商图谱项目-neo4j-高级查询-联合查询.mp4
17-大模型-NLP-电商图谱项目-neo4j-高级查询-子查询.mp4
18-大模型-NLP-电商图谱项目-neo4j-高级查询-高级模型匹配-节点和关系.mp4
18-大模型-NLP-电商图谱项目-neo4j-高级查询-高级模型匹配-路径.mp4
19-大模型-NLP-电商图谱项目-neo4j-约束.mp4
_06
01-大模型-NLP-电商图谱项目-Neo4j-Python驱动-语法说明.mp4
02-大模型-NLP-电商图谱项目-Neo4j-Python驱动-处理结果.mp4
03-大模型-NLP-电商图谱项目-构建知识图谱-课程计划.mp4
04-大模型-NLP-电商图谱项目-构建知识图谱-准备电商数据库.mp4
05-大模型-NLP-电商图谱项目-构建知识图谱-电商核心概念介绍.mp4
06-大模型-NLP-电商图谱项目-构建知识图谱-Neo4J数据建模思路规划.mp4
07-大模型-NLP-电商图谱项目-构建知识图谱-数据库查询练习题说明.mp4
08-大模型-NLP-电商图谱项目-构建知识图谱-数据库查询练习题讲解.mp4
09-大模型-NLP-电商图谱项目-构建知识图谱-明确图数据库数据模型.mp4
10-大模型-NLP-电商图谱项目-构建知识图谱-数据库数据同步-思路说明.mp4
11-大模型-NLP-电商图谱项目-构建知识图谱-数据库数据同步-读取Mysql-上.mp4
12-大模型-NLP-电商图谱项目-构建知识图谱-数据库数据同步-读取Mysql-下.mp4
13-大模型-NLP-电商图谱项目-构建知识图谱-数据库数据同步-写入Neo4j-商品基础信息.mp4
14-大模型-NLP-电商图谱项目-构建知识图谱-数据库数据同步-写入Neo4j-商品属性信息.mp4
15-大模型-NLP-电商图谱项目-构建知识图谱-商品详情图片同步-easyocr介绍.mp4
16-大模型-NLP-电商图谱项目-构建知识图谱-商品详情图片同步-easyocr测试.mp4
17-大模型-NLP-电商图谱项目-构建知识图谱-商品详情图片同步-GPU异常说明.mp4
数据库查询练习题.txt
电商核心概念.drawio
知识图谱项目.drawio
_07
01-大模型-NLP-知识图谱-环境说明.mp4
02-大模型-NLP-知识图谱-数据同步-商品详情图片-思路分析.mp4
03-大模型-NLP-知识图谱-数据同步-商品详情图片-获取图片文本.mp4
04-大模型-NLP-知识图谱-数据同步-商品详情图片-获取商品描述.mp4
05-大模型-NLP-知识图谱-数据同步-UIE模型Bug说明.mp4
06-大模型-NLP-知识图谱-数据同步-商品详情图片-处理UIE结果.mp4
07-大模型-NLP-知识图谱-数据同步-商品详情图片-easyorc加载离线包.mp4
08-大模型-NLP-知识图谱-数据同步-商品详情图片-数据写入-说明.mp4
09-大模型-NLP-知识图谱-数据同步-商品详情图片-数据写入-Optional MATCH说明.mp4
10-大模型-NLP-知识图谱-数据同步-商品详情图片-数据写入-实操.mp4
11-大模型-NLP-知识图谱-数据同步-商品详情图片-整体测试.mp4
12-大模型-NLP-知识图谱-数据同步-用户行为日志.mp4
13-大模型-NLP-知识图谱-数据同步-每日增量同步说明.mp4
14-大模型-NLP-知识图谱-数据同步-neo4j唯一性约束说明.mp4
15-大模型-NLP-知识图谱-图谱应用-思路说明.mp4
16-大模型-NLP-知识图谱-图谱应用-意图识别模型-说明.mp4
17-大模型-NLP-知识图谱-图谱应用-easyocr-远程连接中文路径问题.mp4
图谱项目环境.txt
14_大模型项目实战之AI智教
1.笔记
2.资料
ai-edu
data
edu.sql
images
4
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intent_classify
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mengzi-t5-base
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utils.py
尚硅谷大模型项目实战之AI智教-项目说明.docx
3.代码
15_大模型项目实战之智医助手
1.笔记
2.资料
ai-medical
data
annotated_data
CMeIE-V2.jsonl
intent_classify
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knowledge_graph
medical_kg.jsonl
spell_check
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bert-base-chinese
README.md
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tokenizer.json
tokenizer_config.json
vocab.txt
mengzi-t5-base
config.json
model.safetensors
spiece.model
spiece.vocab
templates
index.html
marked.min.js
purify.min.js
uie_pytorch
LICENSE
convert.py
doccano.md
doccano.py
ernie.py
ernie_m.py
evaluate.py
export_model.py
finetune.py
labelstudio2doccano.py
model.py
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tokenizer.py
uie_base_pytorch
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pytorch_model.bin
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tokenizer_config.json
vocab.txt
uie_predictor.py
utils.py
尚硅谷大模型项目实战之智医助手- 项目说明.docx
3.代码
16_大模型技术之LangChain
1.笔记
01-LangChain使用概述.md
02-LangChain使用之Model IO.md
03-LangChain使用之Chains.md
04-LangChain使用之Memory.md
05-LangChain使用之Tools.md
06-LangChain使用之Agents.md
07-LangChain使用之Retrieval.md
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How-Embeddings-Work.jpg
LCEL-chain.png
LECL.png
RAG架构图.svg
Retrieval-1749995042079.png
Retrieval.png
V0.1.jpg
a3256b256588fa54b6ee72f41b40fb6c.png
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b99061cf66e6d3d7d28ad26bb5eacec4.jpg
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langchain+chatglm.png
langchain的位置.jpg
langchain的位置.png
嵌入模型.png
根据文字画图表.png
2.资料
asset
load
01-langchain-gbk.txt
01-langchain-utf-8.txt
02-load.pdf
03-line.jsonl
03-load.json
03-response.json
04-load.csv
05-load.html
06-load.md
07-fun.py
07-fun_param.py
07-fun_retun.py
07-param_form.py
08-ai.txt
09-ai1.txt
10-test_doc.txt
11-langchain.md
12-test.txt
13-sgg_chat.docx
prompt.json
prompt.yaml
conda使用指南
images
image-20250613160741953.png
image-20250613170613557.png
image-20250613170631040.png
image-20250613170656562.png
image-20250613170804298.png
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image-20250620160612630.png
image-20250620164419520.png
image-20250620164544069.png
image-20250620165046595.png
环境变量.png
终端测试.png
编辑系统环境变量.png
尚硅谷-conda使用指南.md
models.zip
models替换位置.jpg
3.代码
4.视频
01
01
langchain_tutorial
.env
.idea
.gitignore
inspectionProfiles
profiles_settings.xml
langchain_tutorial.iml
misc.xml
modules.xml
vcs.xml
workspace.xml
chapter01_intro
01_Test.py
HelloWorld.ipynb
chapter02_Model_IO
01-LLMInvoke.py
01-模型调用1.ipynb
02-同步与异步的测试.py
02-模型调用2.ipynb
03-模型调用3.ipynb
01-为什么要学习LangChain.mp4
02-LangChain的架构.mp4
03-开发前的准备工作.mp4
04-RAG的架构和执行流程.mp4
05-Agent的架构.mp4
06-大模型开发场景的选择.mp4
07-LangChain几个模块使用的HelloWorld.mp4
08-如何导入现有的某个虚拟环境1.mp4
08-如何导入现有的某个虚拟环境.mp4
09-如何导入现有的某个虚拟环境1.mp4
10-非对话模型与对话模型的举例.mp4
11-调用OpenAI的API和LangChain的API的方式.mp4
12-LangChain如何调用对话模型.mp4
13-其它平台如何调用大模型.mp4
14-大模型调用的总结.mp4
15-对话模型中消息的使用.mp4
16-多种方法调用的演示.mp4
02
01-复习.mp4
02
langchain_tutorial
.env
.idea
.gitignore
inspectionProfiles
profiles_settings.xml
langchain_tutorial.iml
misc.xml
modules.xml
vcs.xml
workspace.xml
chapter01_intro
01_Test.py
HelloWorld.ipynb
chapter02_Model_IO
01-模型调用
01-LLMInvoke.py
01-模型调用1.ipynb
02-同步与异步的测试.py
02-模型调用2.ipynb
03-模型调用3.ipynb
04-大模型的调用.ipynb
02-提示词模板
01-PromptTemplate的使用.ipynb
02-ChatPromptTemplate的使用.ipynb
03-少量示例的提示词模板.ipynb
04-从文件中读取提示词.ipynb
prompt.json
prompt.yaml
03-输出解析器
01-输出解析器的使用.ipynb
04-调用本地的大模型
01-调用本地大模型.ipynb
02-昨天关于消息的一个问题的解释.mp4
03-PrompTemplate的两种实例化方式.mp4
04-partial_variables和partial()的使用.mp4
05-format()与invoke()的对比.mp4
06-结合大模型的调用.mp4
07-ChatPromptTemplate的实例化方式.mp4
08-ChatPromptTemplate的几个方法的调用对比.mp4
09-ChatPromptTemplate的几种不同的参数使用情况.mp4
10-结合大模型的调用.mp4
11-MessagesPlaceholder的使用.mp4
12-FewShotPromptTemplate的使用.mp4
13-FewShotChatMessagePromptTemplate的使用.mp4
14-PiplinePrompTemplate与物理磁盘读取提示词模板.mp4
15-StrOutputParser的使用.mp4
16-JsonOutputParser的使用.mp4
17-其它输出解析器的使用.mp4
18-安装Ollama，并调用本地私有大模型.mp4
03
01-强调一下LangChain的整体实现.mp4
02-LCEL语法中Chain的使用.mp4
03
langchain_tutorial
.env
.idea
.gitignore
inspectionProfiles
profiles_settings.xml
langchain_tutorial.iml
misc.xml
modules.xml
vcs.xml
workspace.xml
chapter01_intro
01_Test.py
HelloWorld.ipynb
chapter02_Model_IO
01-模型调用
01-LLMInvoke.py
01-模型调用1.ipynb
02-同步与异步的测试.py
02-模型调用2.ipynb
03-模型调用3.ipynb
04-大模型的调用.ipynb
02-提示词模板
01-PromptTemplate的使用.ipynb
02-ChatPromptTemplate的使用.ipynb
03-少量示例的提示词模板.ipynb
04-从文件中读取提示词.ipynb
prompt.json
prompt.yaml
03-输出解析器
01-输出解析器的使用.ipynb
04-调用本地的大模型
01-调用本地大模型.ipynb
chapter03_Chain
01-基础Chain的使用.ipynb
02-load.pdf
02-基于LCEL语法的新的Chain.ipynb
chapter04_memory
01-Memory的使用.ipynb
02-Memory的使用.ipynb
chapter05_tools
01-工具的使用.ipynb
03-LLMChain的使用.mp4
04-SimpleSequentialChain的使用.mp4
05-SequentialChain的使用.mp4
06-传统的几个Chain的介绍.mp4
07-基于LCEL语法的新的chain的使用.mp4
08-Memory模块的介绍.mp4
09-ChatMessageHistory的使用.mp4
10-ConversationBufferMemory的基本使用.mp4
11-基于PromptTemplate的ConversationBufferMemory的使用.mp4
12-基于ChatPromptTemplate的ConversationBufferMemory的使用.mp4
13-ConversationChain的使用.mp4
14-ConversationBufferWindowMemory的使用.mp4
15-使用@tool定义一个工具.mp4
16-使用StructuredTool的方式定义工具.mp4
17-工具使用的举例.mp4
04
01-几个其他的Memory的说明.mp4
02-智能体的概述.mp4
03-创建Agent和AgentExecutor的创建方式和AgentTpe的说明.mp4
04
langchain_tutorial
.env
.idea
.gitignore
inspectionProfiles
profiles_settings.xml
langchain_tutorial.iml
misc.xml
modules.xml
vcs.xml
workspace.xml
chapter01_intro
01_Test.py
HelloWorld.ipynb
chapter02_Model_IO
01-模型调用
01-LLMInvoke.py
01-模型调用1.ipynb
02-同步与异步的测试.py
02-模型调用2.ipynb
03-模型调用3.ipynb
04-大模型的调用.ipynb
02-提示词模板
01-PromptTemplate的使用.ipynb
02-ChatPromptTemplate的使用.ipynb
03-少量示例的提示词模板.ipynb
04-从文件中读取提示词.ipynb
prompt.json
prompt.yaml
03-输出解析器
01-输出解析器的使用.ipynb
04-调用本地的大模型
01-调用本地大模型.ipynb
chapter03_Chain
01-基础Chain的使用.ipynb
02-load.pdf
02-基于LCEL语法的新的Chain.ipynb
chapter04_memory
01-Memory的使用.ipynb
02-Memory的使用.ipynb
chapter05_tools
01-工具的使用.ipynb
chapter06_agents
01-传统的方式.ipynb
02-通用的方式.ipynb
03-Agent中使用Memory.ipynb
chapter07_RAG
01-文档加载器的使用.ipynb
asset
load
01-langchain-gbk.txt
01-langchain-utf-8.txt
02-load.pdf
03-line.jsonl
03-load.json
03-response.json
04-load.csv
05-load.html
06-load.md
07-fun.py
07-fun_param.py
07-fun_retun.py
07-param_form.py
08-ai.txt
09-ai1.txt
10-test_doc.txt
11-langchain.md
12-test.txt
13-sgg_chat.docx
prompt.json
prompt.yaml
04-创建Agent和AgentExecutor的流程.mp4
05-案例1：传统方式中的React模式.mp4
06-案例1：传统方式中的FUNCTION_CALL模式.mp4
07-案例2：传统方式中的React模式（多工具的调用）.mp4
08-案例2：传统方式中的FUNCTION_CALL模式（多工具的调用）.mp4
09-案例3：自定义函数的调用.mp4
10-案例4：通用方式中的FUNCTION_CALL模式.mp4
11-案例4：通用方式中的React模式.mp4
12-关于提示词的再说明.mp4
13-方式1：传统的方式体现Memory的使用.mp4
14-方式2：通用的方式体现Memory的使用.mp4
15-RAG的理解与整体的流程.mp4
16-文档加载器的使用.mp4
17_尚硅谷大模型技术之Git
1.笔记
课件-新
Git的安装与使用.md
images
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linus与Git.png
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课件-旧
Git的安装与使用.md
images
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linus与Git.png
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2.资料
Git-2.40.0-64-bit.exe
3.代码
4.视频
01-版本控制工具的概述.mp4
02-Git的介绍和安装.mp4
03-Git的使用的主要内容.mp4
04-Git中如何初始化用户签名.mp4
05-Git中status、add、commit的使用.mp4
06-对比工作区、暂存区、本地库的文件.mp4
07-查看日志信息的指令.mp4
08-版本穿梭的操作.mp4
09-删除文件.mp4
10-分支的创建、切换、合并与冲突的解决.mp4
11-Git与Gitee交互的整体的流程说明.mp4
12-具体的操作1：将本地项目推送到远程Gitee上.mp4
13-操作2中出现的问题的说明.mp4
14-具体的操作2：远程仓库clone到本地等操作.mp4
15-PyCharm中Git的基本操作.mp4
16-PyCharm中分支操作与冲突的解决.mp4
17-PyCharm中关联Gitee并push到远程仓库.mp4
18-Pycharm中pull远程仓库的代码到本地.mp4
19-Pycharm中clone操作.mp4
代码
Git_Demo
.idea
.gitignore
Git_Demo.iml
inspectionProfiles
profiles_settings.xml
misc.xml
modules.xml
vcs.xml
workspace.xml
module01
Hello.py
__init__.py
git_projects
git_project1
hello1.txt
hello2.txt
gitee_project1
hello1.txt
lisi
gitee-pro
hello1.txt
gitee-pro1
hello1.txt
18_尚硅谷大模型技术之大模型微调核心
1.笔记
01_尚硅谷大模型技术之主流大模型原理v1.0.docx
02_尚硅谷大模型技术之微调理论v1.0.docx
2.资料
GPT-1架构-细节.drawio
部分原理实现代码.txt
3.代码
4.视频
01
01_原理_基本特点.mp4
02_原理_模型的开源.mp4
03_原理_大模型的开源现状.mp4
04_原理_常用网站推荐.mp4
05_GPT_模型发布时间线.mp4
06_GPT_前置知识回顾.mp4
07_GPT_前置知识_Adam回顾.mp4
08_GPT_前置知识_Adam和L2的问题.mp4
09_GPT_前置知识_AdamW.mp4
10_GPT_概述.mp4
11_GPT_与transformer总体对比.mp4
12_GPT_与transformer总体对比2.mp4
13_GPT_预训练阶段总体认识.mp4
14_GPT_微调阶段总体认识.mp4
15_GPT_微调细节梳理_掩码自注意力子层.mp4
16_GPT_微调细节熟悉_FFN子层.mp4
17_GPT_微调细节熟悉_输出的处理和融合.mp4
18_GPT_参数量计算.mp4
19_当日小结.mp4
02
01_每日一考.mp4
02_GPT2_概述.mp4
03_GPT2_概述2.mp4
04_GPT2_与GPT1的主要区别.mp4
05_GPT2_层归一化位置的对比分析.mp4
06_GPT2_小结.mp4
07_GPT3_概述.mp4
08_GPT3_元学习.mp4
09_GPT3_与GPT2的区别.mp4
10_GPT3_稀疏与稠密的含义.mp4
11_GPT3_稠密的代价.mp4
12_GPT3_二维分解注意力.mp4
13_GPT3_稀疏的效果.mp4
14_GPT3_稀疏的补充说明.mp4
15_InstructGPT_概述&扫盲.mp4
16_InstructGPT_训练流程.mp4
17_InstructGPT_PPO-ptx.mp4
18_GPT发展梳理&系列产品.mp4
19_LLama_发展历史&LLama1概述.mp4
20_LLama1_与transformer区别.mp4
21_LLama1_架构优化1.mp4
22_LLama1_架构优化2.mp4
23_LLama2_分组查询注意力.mp4
03
01_每日一考.mp4
02_Llama-chat_总体训练流程.mp4
03_Llama-chat_奖励模型&拒绝采样.mp4
04_Llama3_主要改进.mp4
05_Llama3_预训练阶段.mp4
06_Llama3_关于数据质量的重要性.mp4
07_Llama3_模型架构.mp4
08_Llama3_缩放定律1.mp4
09_Llama3_缩放定律2.mp4
10_Llama3_后训练总体流程&数据准备.mp4
11_Llama3_后训练流程.mp4
12_Llama3_小结.mp4
13_Qwen3_前置知识_思维链.mp4
14_Qwen3_稠密架构.mp4
15_Qwen3_MOE模型.mp4
16_关于模型结构的代码学习参考.mp4
17_Qwen3_预训练流程.mp4
18_Qwen3_后训练流程.mp4
每日一考02.txt
19_尚硅谷大模型技术之企业级LLM部署与RAG&Agent开发实战
1.笔记
笔记1
images
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第1章：企业级大模型的部署.md
第2章：Dify构建企业级RAG与Agent应用.md
笔记2
01-企业私有&个人知识库的搭建.md
02-基于Coze&Dify平台的智能体开发.md
Coze案例：一键生成行业调研PPT.md
Coze案例：复刻爆款视频.md
Coze案例：根据官方模板复刻应用：海报.md
Dify案例：生成深度专题论文.md
Dify的Windows平台部署.md
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个人知识库流程-1754883509018.jpg
个人知识库流程.jpg
笔记3
Dify案例：一键生成行业调研报告.md
Python调用Coze平台工作流.md
Python调用Dify平台工作流.md
images
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AI Agent架构图-1740364061717-4.svg
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个人知识库流程-1754883509018.jpg
个人知识库流程.jpg
2.资料
资料1
AutoDL使用文档.pdf
Xshell-8.0.0057p.exe
finalshell_windows_x64.exe
使用讲师共享的镜像的操作步骤.txt
刑法.txt
资料2
Cherry-Studio-1.5.5-x64-setup.exe
ima.copilot-win-x64-10000028-1.10.0(3007).exe
一键生成行业调研报告.yml
北京市高考试卷
2025年高考北京卷数学历年真题试卷.docx
年北京市高考数学卷含答案..docx
年北京市高考数学试卷-(答案与解析).doc
年北京市高考数学试卷含答案解析(原卷版).doc
年高考数学真题试卷(北京卷)附详细解答.docx
抖音编程文案-康师傅
AI的火爆，会不会让程序员大量失业.docx
C语言到底要不要学？.docx
Java转GO，是越走越窄，还是柳暗花明？.docx
Python：非专业开发的首选语言？.docx
云计算运维：这其实算是俩方向.docx
人工智能：看看2025年高薪机遇.docx
什么人适合学习Go.docx
剖析Java死不透的底层逻辑.docx
听说Java入行要学很多技术栈，零基础，非科班，如何规划学习？.docx
哪些人适合入手C++.docx
已经从事软件开发，要不要转投鸿蒙？.docx
想入行软件开发，不知道选啥语言？.docx
成为Java工程师，要掌握全栈、分布式、嵌入式和C++吗？.docx
网络&信息安全：想说爱你不容易.docx
计科相关专业的哪些课程比较重要呢.docx
智能体的交互.mp4
讯飞星火_1.10.32.exe
3.代码
4.视频
01
01-为何需要企业级部署大模型.mp4
02-大模型的应用场景：RAG、Agent.mp4
03-整体要部署的三条主线.mp4
04-腾讯云服务器的部署.mp4
05-部署docker.mp4
06-部署dify.mp4
07-访问dify_体会配置deepseek大模型.mp4
08-使用老师共享的镜像的方式如何启动dify.mp4
09-创建AutoDL上的实例并通过XShell连接.mp4
10-ollama的下载.mp4
11-ollama下下载选中的大模型.mp4
12-Dify中接入Ollama中的大语言模型.mp4
13-新建的AutoDL服务器实例上安装Xinference及嵌入&重排序模型.mp4
14-Dify添加Ollama的大语言模型出现的问题的解决.mp4
15-Dify平台打通隧道_添加嵌入&重排序模型.mp4
16-如何使用部署好的模型.mp4
02
01-课程的介绍.mp4
02-个人知识库的概述.mp4
03-CherryStudio的个人知识库的搭建.mp4
04-ima平台构造知识库.mp4
05-智能体概述_3种不同层次的智能体.mp4
06-level 1级别的智能体的开发.mp4
07-level3级别中coze平台的介绍.mp4
08-coze平台搭建智能体1：深夜情感主持1.mp4
09-coze平台搭建智能体1：深夜情感主持2.mp4
10-coze平台搭建智能体2：高校百事通.mp4
11-coze平台搭建智能体3：家庭记账助手.mp4
12-Dify平台配置大模型.mp4
13-Dify平台构建智能体：英语学习助手.mp4
14-coze工作流之复刻爆款视频的说明.mp4
15-coze工作流之复刻爆款视频的工作流.mp4
16-coze工作流之复刻爆款视频的用户界面的设置.mp4
17-coze工作流之生成行业ppt的实现.mp4
18-明天我们要做的3个事.mp4
03
01-今天的三个任务.mp4
02-Dify平台工作流的准备工作：工具的授权_大模型的配置.mp4
03-Dify平台工作流：一键生成行业深度报告1.mp4
04-Dify平台工作流：一键生成行业深度报告2.mp4
05-Dify平台API的讲解与Postman的请求说明.mp4
06-Python程序调用Dify的工作流.mp4
07-Python程序调用Coze的工作流.mp4
08-实战的任务书说明.mp4
Dify_Coze_Demo.zip
实战
实战-任务书
Coze_一键生成行业调研报告任务书
Coze_一键生成行业调研报告任务书.md
images
image-20250814163523944.png
image-20250814163746448.png
image-20250814223336721.png
Dify_一键生成PPT任务书
Dify_一键生成PPT任务书.md
images
image-20250814112652313.png
Dify_复刻爆款视频任务书
Dify_复刻爆款视频任务书.md
images
image-20250814112002347.png
实战-最终实现
Coze_一键生成行业调研报告
Coze_一键生成行业调研报告.md
images
image-20250814155413876.png
image-20250814155852711.png
image-20250814160013810.png
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Dify_一键生成PPT
Dify_一键生成PPT.md
Dify_一键生成PPT.yml
images
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Dify_复刻爆款视频
Dify_复刻爆款视频.md
Dify_复刻爆款视频.yml
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20_尚硅谷大模型技术之大模型微调理论与实战
01_笔记
01_尚硅谷大模型技术之微调核心理论v1.1.docx
02_尚硅谷大模型技术之微调实战v1.1.docx
02_资料
03_代码
04_视频
01
00_课前说明.mp4
01_硬件基础_GPU.mp4
02_硬件基础_显卡.mp4
03_硬件基础_CUDA_线程模型与执行.mp4
04_硬件基础_CUDA内存&对比.mp4
05_微调技术_微调流程.mp4
06_微调技术_模型来源&数据来源.mp4
07_微调技术_方法分类&数据类型.mp4
08_微调技术_fp16的下溢出问题.mp4
09_微调技术_fp16的舍入误差问题.mp4
10_微调技术_混合精度训练_fp32副本.mp4
11_微调技术_混合精度训练_损失缩放.mp4
12_微调技术_模型规模_混合精度训练权重显存计算.mp4
13_微调技术_模型规模_隐藏层&所需总显存.mp4
14_微调技术_并行技术_理论.mp4
15_微调技术_并行技术_DP的通讯优化补充.mp4
16_微调技术_并行技术_分布式训练框架deepspeed.mp4
17_微调技术_PEFT_LoRA总体概述.mp4
18_微调技术_PEFT_LoRA细节梳理.mp4
19_微调技术_PEFT_QLoRA_NF4.mp4
20_微调技术_PEFT_QLoRA_二次量化.mp4
02
01_数据集
keywords_data_train.jsonl
psychology_data.jsonl
01_每日一考.mp4
01代码.zip
02_lora_环境准备&模型下载.mp4
03_lora_unsloth_安装依赖&加载模型.mp4
04_lora_unsloth_加载数据&处理格式.mp4
05_lora_unsloth_开启batch的验证.mp4
05_每日一考
每日一考01.txt
06_进度回顾与数据批处理回顾.mp4
07_lora_unsloth_添加lora和SFTTrainer.mp4
08_lora_unsloth_Trainer参数配置.mp4
09_lora_unsloth_保存结果&运行日志介绍.mp4
10_lora_unsloth_推理代码思路.mp4
11_lora_unsloth_推理代码解析.mp4
12_lora_unsloth_启动训练&日志解析.mp4
关于dataset的批处理说明.txt
LeetCode 101 - A Grinding Guide.pdf
姜夏老师AI大模型深度学习串讲
视频
01-算法工程师的日常工作.mp4
02-大家关心的问题01.mp4
03-大家关心的问题02.mp4
04-豆包的使用.mp4
05-开源数据集使用.mp4
06-课间提问.mp4
07-划重点.mp4
08-学习建议.mp4
09-课间问题01.mp4
Attention is all you need.pdf
串讲笔记.txt
深度学习阶段.pdf
没有视频的文件是自习课，自己做作业的
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