udemy-机器学习和数据科学训练营

📁 9 - Scikitlearn Creating Machine Learning Models
    9 - Scikitlearn Creating Machine Learning Models文档.png  [493.5 KB]
    98 - Section Overview.srt  [4.3 KB]
    136 - Machine Learning Model Evaluation.html  [7.1 KB]
    138 - NEW Evaluating A Model With Scikitlearn Functions.srt  [19.2 KB]
    99 - Introduction to ScikitLearn Jupyter Notebook with annotations.txt  [130.0 B]
    148 - Putting It All Together 2.mp4  [211.3 MB]
    143 - Note Metric Comparison Improvement.html  [2.2 KB]
    114 - ScikitLearn machine learning map how to choose the right machine learning model【微信号 itcodeba 】.txt  [72.0 B]
    110 - Getting Your Data Ready Handling Missing Values With Pandas.mp4  [186.8 MB]
    126 - Evaluating A Classification Model 1 Accuracy.srt  [6.5 KB]
    104 - Example ScikitLearn Workflow Notebook.txt  [131.0 B]
    113 - Getting Your Data Ready Handling Missing Values With Scikitlearn.srt  [24.8 KB]
    99 - Scikitlearn Introduction.srt  [10.6 KB]
    115 - NEW Choosing The Right Model For Your Data 2 Regression.srt  [15.7 KB]
    101 - Refresher What Is Machine Learning.srt  [6.4 KB]
    113 - Getting Your Data Ready Handling Missing Values With Scikitlearn.mp4  [241.4 MB]
    120 - Making Predictions With Our Model.srt  [12.9 KB]
    133 - NEW Evaluating A Regression Model 1 R2 Score.srt  [13.9 KB]
    99 - Scikitlearn Introduction.mp4  [26.6 MB]
    106 - Getting Your Data Ready Splitting Your Data.mp4  [109.0 MB]
    103 - ScikitLearn Reference Notebook.txt  [133.0 B]
    118 - Choosing The Right Model For Your Data 3 Classification.mp4  [216.3 MB]
    124 - NEW Evaluating A Machine Learning Model Score Part 2.mp4  [115.2 MB]
    100 - Quick Note Upcoming Video.html  [390.0 B]
    134 - NEW Evaluating A Regression Model 2 MAE.mp4  [74.0 MB]
    105 - Optional Debugging Warnings In Jupyter.srt  [26.8 KB]
    121 - predict vs predictproba.srt  [12.3 KB]
    146 - Saving And Loading A Model 2.mp4  [85.9 MB]
    132 - Evaluating A Classification Model 6 Classification Report.srt  [14.9 KB]
    140 - Tuning Hyperparameters.srt  [32.8 KB]
    144 - Quick Tip Correlation Analysis.srt  [2.9 KB]
    126 - Evaluating A Classification Model 1 Accuracy.mp4  [45.6 MB]
    105 - Optional Debugging Warnings In Jupyter.mp4  [322.1 MB]
    145 - Saving And Loading A Model.mp4  [91.3 MB]
    110 - Getting Your Data Ready Handling Missing Values With Pandas.srt  [18.7 KB]
    124 - NEW Evaluating A Machine Learning Model Score Part 2.srt  [9.2 KB]
    134 - NEW Evaluating A Regression Model 2 MAE.srt  [9.3 KB]
    98 - Section Overview.mp4  [8.6 MB]
    135 - NEW Evaluating A Regression Model 3 MSE.srt  [13.2 KB]
    144 - Quick Tip Correlation Analysis.mp4  [30.9 MB]
    137 - NEW Evaluating A Model With Cross Validation and Scoring Parameter.srt  [34.2 KB]
    138 - NEW Evaluating A Model With Scikitlearn Functions.mp4  [241.3 MB]
    123 - NEW Evaluating A Machine Learning Model Score Part 1.srt  [14.2 KB]
    131 - NEW Evaluating A Classification Model 5 Confusion Matrix.mp4  [189.6 MB]
    148 - Introduction to ScikitLearn Jupyter Notebook from the videos.txt  [136.0 B]
    120 - Making Predictions With Our Model.mp4  [117.9 MB]
    107 - Quick Tip Clean Transform Reduce.mp4  [20.2 MB]
    102 - Quick Note Upcoming Videos.html  [1018.0 B]
    123 - NEW Evaluating A Machine Learning Model Score Part 1.mp4  [153.2 MB]
    121 - predict vs predictproba.mp4  [56.5 MB]
    130 - Notebook from video with updated confusion matrix labels.txt  [130.0 B]
    135 - NEW Evaluating A Regression Model 3 MSE.mp4  [161.6 MB]
    137 - NEW Evaluating A Model With Cross Validation and Scoring Parameter.mp4  [410.2 MB]
    99 - ScikitLearn Documentation.txt  [47.0 B]
    117 - Quick Tip How ML Algorithms Work.srt  [1.9 KB]
    104 - Typical scikitlearn Workflow.mp4  [335.9 MB]
    140 - Tuning Hyperparameters.mp4  [118.9 MB]
    148 - Introduction to ScikitLearn Jupyter Notebook with annotations.txt  [130.0 B]
    141 - Tuning Hyperparameters 2.srt  [18.1 KB]
    125 - Evaluating A Machine Learning Model 2 Cross Validation.srt  [18.1 KB]
    117 - Quick Tip How ML Algorithms Work.mp4  [10.9 MB]
    147 - Putting It All Together.mp4  [261.1 MB]
    108 - Getting Your Data Ready Convert Data To Numbers.mp4  [236.9 MB]
    112 - Note Correction in the upcoming video splitting data.html  [2.2 KB]
    111 - Extension Feature Scaling.html  [2.9 KB]
    106 - scikit-learn-data.zip  [20.8 KB]
    142 - Tuning Hyperparameters 3.mp4  [212.1 MB]
    99 - Introduction to ScikitLearn Jupyter Notebook from the upcoming videos.txt  [136.0 B]
    139 - Improving A Machine Learning Model.srt  [14.3 KB]
    141 - Tuning Hyperparameters 2.mp4  [202.7 MB]
    116 - Quick Note Decision Trees.html  [221.0 B]
    127 - Evaluating A Classification Model 2 ROC Curve.mp4  [113.7 MB]
    115 - NEW Choosing The Right Model For Your Data 2 Regression.mp4  [239.9 MB]
    108 - Getting Your Data Ready Convert Data To Numbers.srt  [24.5 KB]
    109 - Note Update to next video OneHotEncoder can handle NaNNone values.html  [1.5 KB]
    147 - Putting It All Together.srt  [28.6 KB]
    139 - Improving A Machine Learning Model.mp4  [161.3 MB]
    106 - Getting Your Data Ready Splitting Your Data.srt  [12.2 KB]
    128 - Evaluating A Classification Model 3 ROC Curve.mp4  [85.3 MB]
    130 - Evaluating A Classification Model 4 Confusion Matrix.srt  [16.8 KB]
    101 - Refresher What Is Machine Learning.mp4  [33.4 MB]
    107 - Quick Tip Clean Transform Reduce.srt  [6.5 KB]
    130 - Evaluating A Classification Model 4 Confusion Matrix.mp4  [136.2 MB]
    119 - Fitting A Model To The Data.mp4  [100.8 MB]
    129 - Reading Extension ROC Curve AUC.html  [1.5 KB]
    114 - NEW Choosing The Right Model For Your Data.mp4  [435.2 MB]
    128 - Evaluating A Classification Model 3 ROC Curve.srt  [10.6 KB]
    119 - Fitting A Model To The Data.srt  [9.6 KB]
    127 - Evaluating A Classification Model 2 ROC Curve.srt  [12.6 KB]
    146 - Saving And Loading A Model 2.srt  [9.7 KB]
    104 - Typical scikitlearn Workflow.srt  [34.3 KB]
    118 - Choosing The Right Model For Your Data 3 Classification.srt  [19.6 KB]
    148 - Putting It All Together 2.srt  [16.3 KB]
    122 - NEW Making Predictions With Our Model Regression.srt  [12.2 KB]
    114 - NEW Choosing The Right Model For Your Data.srt  [29.9 KB]
    122 - NEW Making Predictions With Our Model Regression.mp4  [145.9 MB]
    131 - NEW Evaluating A Classification Model 5 Confusion Matrix.srt  [20.3 KB]
    103 - Scikitlearn Cheatsheet.srt  [9.8 KB]
    103 - Scikitlearn Cheatsheet.mp4  [75.1 MB]
    147 - Reading extension ScikitLearns Pipeline class explained.txt  [85.0 B]
📁 15 - Storytelling Communication How To Present Your Work
    15 - Storytelling Communication How To Present Your Work说明.png  [493.5 KB]
    252 - Section Overview.mp4  [11.4 MB]
    256 - Weekend Project Principle.srt  [9.1 KB]
    256 - Weekend Project Principle.mp4  [14.8 MB]
    254 - Communicating With Managers.srt  [4.1 KB]
    259 - Communicating and sharing your work Further reading.html  [3.1 KB]
    258 - Storytelling.srt  [4.1 KB]
    257 - Devblog by Hashnode an easy and free way to create a blog you own.txt  [28.0 B]
    253 - How to Think About Communicating and Sharing Your Work blog post.txt  [81.0 B]
    255 - Communicating With CoWorkers.srt  [5.1 KB]
    253 - Communicating Your Work.srt  [4.8 KB]
    253 - Communicating Your Work.mp4  [21.1 MB]
    258 - Storytelling.mp4  [6.9 MB]
    257 - Communicating With Outside World.mp4  [9.2 MB]
    255 - Communicating With CoWorkers.mp4  [11.4 MB]
    252 - Section Overview.srt  [3.1 KB]
    254 - Communicating With Managers.mp4  [10.9 MB]
    257 - Communicating With Outside World.srt  [4.4 KB]
    257 - fasttemplate by fastai a template you can use for your blog on GitHub Pages.txt  [45.0 B]
📁 19 - Extra Learn Advanced Statistics and Mathematics for FREE
    19 - Extra Learn Advanced Statistics and Mathematics for FREE资料.png  [493.5 KB]
    374 - Statistics and Mathematics.html  [710.0 B]
📁 21 - BONUS SECTION
    21 - BONUS SECTION必看.png  [493.5 KB]
    378 - Special Bonus Lecture.html  [1.2 KB]
📁 6 - Pandas Data Analysis
    6 - Pandas Data Analysis必看.zip  [1.8 MB]
    54 - Jake VanderPlass Data Manipulation with Pandas.txt  [85.0 B]
    53 - Selecting and Viewing Data with Pandas Part 2.srt  [18.9 KB]
    58 - Google Colab.txt  [34.0 B]
    54 - car-sales-missing-data.csv  [287.0 B]
    48 - Introduction to Pandas Jupyter Notebook from the upcoming videos.txt  [130.0 B]
    48 - 10 minutes to pandas from the documentation.txt  [70.0 B]
    49 - Series Data Frames and CSVs.mp4  [165.3 MB]
    50 - Data from URLs.html  [1.1 KB]
    49 - pandas-anatomy-of-a-dataframe.png  [333.2 KB]
    58 - How To Download The Course Assignments.mp4  [120.0 MB]
    54 - Manipulating Data.mp4  [68.8 MB]
    47 - Downloading Workbooks and Assignments.html  [967.0 B]
    56 - Introduction to Pandas Jupyter Notebook with annotations.txt  [124.0 B]
    55 - Manipulating Data 2.mp4  [155.3 MB]
    53 - Selecting and Viewing Data with Pandas Part 2.mp4  [186.5 MB]
    51 - Describing Data with Pandas.srt  [13.7 KB]
    48 - Pandas Introduction.mp4  [17.7 MB]
    58 - Course notebooks Github.txt  [47.0 B]
    55 - pandas-anatomy-of-a-dataframe.png  [333.2 KB]
    46 - Section Overview.srt  [3.5 KB]
    48 - Introduction to Pandas Jupyter Notebook with annotations.txt  [124.0 B]
    56 - Introduction to Pandas Jupyter Notebook from the videos.txt  [130.0 B]
    51 - Describing Data with Pandas.mp4  [111.8 MB]
    54 - Manipulating Data.srt  [19.5 KB]
    46 - Section Overview.mp4  [11.3 MB]
    52 - Selecting and Viewing Data with Pandas.srt  [16.3 KB]
    56 - Manipulating Data 3.mp4  [137.0 MB]
    52 - Selecting and Viewing Data with Pandas.mp4  [86.1 MB]
    49 - car-sales.csv  [369.0 B]
    58 - How To Download The Course Assignments.srt  [11.1 KB]
    56 - Manipulating Data 3.srt  [14.3 KB]
    49 - Series Data Frames and CSVs.srt  [18.3 KB]
    55 - Manipulating Data 2.srt  [16.2 KB]
    52 - car-sales.csv  [369.0 B]
    57 - Assignment Pandas Practice.html  [2.1 KB]
    48 - Pandas Introduction.srt  [6.6 KB]
    48 - Pandas Documentation.txt  [45.0 B]
📁 8 - Matplotlib Plotting and Data Visualization
    8 - Matplotlib Plotting and Data Visualization文档.zip  [1.8 MB]
    96 - Saving And Sharing Your Plots.srt  [6.1 KB]
    93 - Plotting from Pandas DataFrames 7.mp4  [220.0 MB]
    81 - matplotlib-anatomy-of-a-plot.png  [369.4 KB]
    85 - Quick Tip Data Visualizations.srt  [2.3 KB]
    90 - Plotting from Pandas DataFrames 4.srt  [10.6 KB]
    79 - Matplotlib Introduction.mp4  [34.7 MB]
    86 - Plotting From Pandas DataFrames.mp4  [89.4 MB]
    82 - Scatter Plot And Bar Plot.srt  [16.4 KB]
    91 - Plotting from Pandas DataFrames 5.srt  [11.9 KB]
    90 - heart-disease.csv  [11.1 KB]
    96 - Saving And Sharing Your Plots.mp4  [92.6 MB]
    85 - Quick Tip Data Visualizations.mp4  [8.3 MB]
    80 - Importing And Using Matplotlib.srt  [17.9 KB]
    94 - Customizing Your Plots.mp4  [161.1 MB]
    79 - Matplotlib Documentation.txt  [42.0 B]
    88 - Plotting From Pandas DataFrames 2.srt  [14.8 KB]
    89 - Plotting from Pandas DataFrames 3.mp4  [127.1 MB]
    81 - Anatomy Of A Matplotlib Figure.mp4  [119.3 MB]
    86 - Plotting From Pandas DataFrames.srt  [9.8 KB]
    78 - Section Overview.srt  [2.5 KB]
    93 - Plotting from Pandas DataFrames 7.srt  [16.8 KB]
    92 - Plotting from Pandas DataFrames 6.mp4  [121.0 MB]
    89 - Plotting from Pandas DataFrames 3.srt  [12.1 KB]
    91 - Plotting from Pandas DataFrames 5.mp4  [92.8 MB]
    87 - Quick Note Regular Expressions.html  [632.0 B]
    96 - Introduction to Matplotlib Notebook from the videos.txt  [134.0 B]
    92 - Plotting from Pandas DataFrames 6.srt  [12.2 KB]
    82 - Scatter Plot And Bar Plot.mp4  [95.5 MB]
    94 - Customizing Your Plots.srt  [15.0 KB]
    95 - Customizing Your Plots 2.mp4  [123.6 MB]
    88 - Plotting From Pandas DataFrames 2.mp4  [176.8 MB]
    79 - Introduction to Matplotlib Jupyter Notebook from the upcoming videos.txt  [134.0 B]
    80 - Importing And Using Matplotlib.mp4  [146.6 MB]
    84 - Subplots Option 2.srt  [7.0 KB]
    79 - Matplotlib Introduction.srt  [7.8 KB]
    90 - Plotting from Pandas DataFrames 4.mp4  [53.1 MB]
    78 - Section Overview.mp4  [6.0 MB]
    97 - Assignment Matplotlib Practice.html  [2.1 KB]
    81 - matplotlib-anatomy-of-a-plot-with-code.png  [654.8 KB]
    81 - Anatomy Of A Matplotlib Figure.srt  [15.4 KB]
    95 - Customizing Your Plots 2.srt  [14.7 KB]
    84 - Subplots Option 2.mp4  [54.3 MB]
    83 - Histograms And Subplots.srt  [14.5 KB]
    83 - Histograms And Subplots.mp4  [116.5 MB]
📁 11 - Milestone Project 1 Supervised Learning Classification
    11 - Milestone Project 1 Supervised Learning Classification说明.png  [493.5 KB]
    166 - Tuning Hyperparameters 2.srt  [16.3 KB]
    170 - Evaluating Our Model 2.srt  [8.2 KB]
    154 - Optional Windows Project Environment Setup.mp4  [58.8 MB]
    165 - Tuning Hyperparameters.srt  [15.2 KB]
    173 - Endtoend Heart Disease Classification Notebook with annotations.txt  [140.0 B]
    155 - Step 14 Framework Setup.srt  [16.8 KB]
    157 - heart-disease.csv  [11.1 KB]
    152 - Endtoend Heart Disease Classification Notebook same as in videos.txt  [146.0 B]
    153 - Project Environment Setup.srt  [16.2 KB]
    153 - Project Environment Setup.mp4  [174.0 MB]
    151 - Section Overview.srt  [3.1 KB]
    166 - Tuning Hyperparameters 2.mp4  [188.1 MB]
    154 - Optional Windows Project Environment Setup.srt  [5.2 KB]
    168 - Quick Note Confusion Matrix Labels.html  [1.1 KB]
    171 - Evaluating Our Model 3.mp4  [111.9 MB]
    160 - Finding Patterns 3.srt  [20.2 KB]
    172 - Finding The Most Important Features.srt  [24.0 KB]
    157 - Exploring Our Data.mp4  [118.9 MB]
    152 - Project Overview.srt  [10.1 KB]
    155 - Step 14 Framework Setup.mp4  [190.8 MB]
    171 - Evaluating Our Model 3.srt  [12.9 KB]
    158 - Finding Patterns.srt  [13.3 KB]
    152 - Project Overview.mp4  [27.0 MB]
    164 - TuningImproving Our Model.srt  [18.3 KB]
    173 - Endtoend Heart Disease Classification Notebook same as in videos.txt  [146.0 B]
    158 - Finding Patterns.mp4  [106.5 MB]
    161 - Preparing Our Data For Machine Learning.mp4  [128.9 MB]
    164 - TuningImproving Our Model.mp4  [102.8 MB]
    152 - Endtoend Heart Disease Classification Notebook with annotations.txt  [140.0 B]
    173 - Reviewing The Project.mp4  [156.9 MB]
    157 - Exploring Our Data.srt  [11.7 KB]
    156 - Getting Our Tools Ready.mp4  [142.3 MB]
    167 - Tuning Hyperparameters 3.mp4  [113.2 MB]
    170 - Evaluating Our Model 2.mp4  [71.0 MB]
    156 - Getting Our Tools Ready.srt  [12.5 KB]
    167 - Tuning Hyperparameters 3.srt  [9.6 KB]
    160 - Finding Patterns 3.mp4  [248.7 MB]
    162 - Choosing The Right Models.mp4  [174.8 MB]
    163 - Experimenting With Machine Learning Models.srt  [9.7 KB]
    162 - Choosing The Right Models.srt  [13.9 KB]
    169 - Evaluating Our Model.srt  [16.5 KB]
    151 - Section Overview.mp4  [7.0 MB]
    159 - Finding Patterns 2.srt  [22.7 KB]
    172 - Finding The Most Important Features.mp4  [222.6 MB]
    165 - Tuning Hyperparameters.mp4  [77.5 MB]
    161 - Preparing Our Data For Machine Learning.srt  [13.1 KB]
    169 - Evaluating Our Model.mp4  [122.8 MB]
    159 - Finding Patterns 2.mp4  [51.6 MB]
    163 - Experimenting With Machine Learning Models.mp4  [100.1 MB]
    152 - Structured Data Projects on GitHub.txt  [94.0 B]
    173 - Reviewing The Project.srt  [14.7 KB]
📁 12 - Milestone Project 2 Supervised Learning Time Series Data
    12 - Milestone Project 2 Supervised Learning Time Series Data文档.png  [493.5 KB]
    180 - Exploring Our Data 2.mp4  [90.8 MB]
    178 - Step 14 Framework Setup.mp4  [155.1 MB]
    175 - Endtoend Bluebook Bulldozer Regression Notebook with annotations.txt  [147.0 B]
    177 - Project Environment Setup.mp4  [179.0 MB]
    175 - Kaggle Bluebook for Bulldozers Competition.txt  [57.0 B]
    182 - Turning Data Into Numbers.mp4  [265.8 MB]
    190 - RandomizedSearchCV.mp4  [155.5 MB]
    190 - RandomizedSearchCV.srt  [13.0 KB]
    175 - Project Overview.mp4  [22.1 MB]
    192 - Preproccessing Our Data.mp4  [258.8 MB]
    194 - Endtoend Bluebook Bulldozer Regression Notebook with annotations.txt  [147.0 B]
    188 - Custom Evaluation Function.srt  [16.3 KB]
    174 - Section Overview.srt  [1.9 KB]
    182 - Turning Data Into Numbers.srt  [24.6 KB]
    186 - Splitting Data.srt  [13.8 KB]
    183 - Filling Missing Numerical Values.mp4  [190.1 MB]
    179 - Exploring Our Data.mp4  [251.4 MB]
    180 - Exploring Our Data 2.srt  [8.7 KB]
    187 - Challenge Whats wrong with splitting data after filling it.html  [1.7 KB]
    185 - Fitting A Machine Learning Model.mp4  [95.8 MB]
    174 - Section Overview.mp4  [15.8 MB]
    189 - Reducing Data.mp4  [168.6 MB]
    175 - Project Overview.srt  [6.9 KB]
    176 - Downloading the data for the next two projects.html  [1.6 KB]
    184 - Filling Missing Categorical Values.mp4  [117.7 MB]
    178 - Step 14 Framework Setup.srt  [12.2 KB]
    192 - Preproccessing Our Data.srt  [18.9 KB]
    191 - Improving Hyperparameters.mp4  [144.2 MB]
    181 - Feature Engineering.srt  [24.2 KB]
    179 - Exploring Our Data.srt  [21.9 KB]
    186 - Splitting Data.mp4  [146.0 MB]
    191 - Improving Hyperparameters.srt  [11.7 KB]
    183 - Filling Missing Numerical Values.srt  [18.1 KB]
    183 - Pandas Categorical Datatype Documentation.txt  [82.0 B]
    184 - Filling Missing Categorical Values.srt  [11.8 KB]
    193 - Making Predictions.srt  [11.8 KB]
    177 - Project Environment Setup.srt  [16.5 KB]
    189 - Reducing Data.srt  [16.5 KB]
    194 - Feature Importance.mp4  [254.0 MB]
    185 - Fitting A Machine Learning Model.srt  [10.5 KB]
    175 - Structured Data Projects on GitHub.txt  [94.0 B]
    194 - Feature Importance.srt  [18.3 KB]
    188 - Custom Evaluation Function.mp4  [184.0 MB]
    193 - Making Predictions.mp4  [142.1 MB]
    181 - Feature Engineering.mp4  [290.8 MB]
    194 - Endtoend Bluebook Bulldozer Regression Notebook same as in videos.txt  [153.0 B]
    175 - Endtoend Bluebook Bulldozer Regression Notebook same as in videos.txt  [153.0 B]
📁 1 - Introduction
    1 - Introduction必看.png  [493.5 KB]
    3 - Exercise Meet Your Classmates and Instructor.html  [3.7 KB]
    1 - Course Outline.mp4  [77.3 MB]
    2 - Join Our Online Classroom.srt  [5.6 KB]
    4 - Your First Day.srt  [5.5 KB]
    2 - Join Our Online Classroom.mp4  [151.6 MB]
📁 2 - Machine Learning 101
    2 - Machine Learning 101说明.png  [493.5 KB]
    7 - Exercise Machine Learning Playground.srt  [8.2 KB]
    8 - How Did We Get Here.mp4  [30.5 MB]
    7 - Exercise Machine Learning Playground.mp4  [42.6 MB]
    5 - What Is Machine Learning.srt  [8.4 KB]
    11 - Are You Getting It Yet.html  [160.0 B]
    6 - AIMachine LearningData Science.srt  [5.9 KB]
    9 - Exercise YouTube Recommendation Engine.srt  [5.6 KB]
    13 - Section Review.mp4  [4.0 MB]
    12 - What Is Machine Learning Round 2.mp4  [18.9 MB]
    14 - Monthly Coding Challenges Free Resources and Guides.html  [1.6 KB]
    9 - Exercise YouTube Recommendation Engine.mp4  [12.9 MB]
    10 - Types of Machine Learning.mp4  [14.8 MB]
    12 - What Is Machine Learning Round 2.srt  [5.4 KB]
    13 - Section Review.srt  [2.3 KB]
    10 - Types of Machine Learning.srt  [5.0 KB]
    8 - How Did We Get Here.srt  [7.1 KB]
    6 - AIMachine LearningData Science.mp4  [19.7 MB]
    5 - What Is Machine Learning.mp4  [28.3 MB]
    9 - Machine Learning Playground.txt  [27.0 B]
    7 - Teachable Machine.txt  [40.0 B]
📁 3 - Machine Learning and Data Science Framework
    16 - Introducing Our Framework.srt  [3.4 KB]
    20 - Types of Evaluation.srt  [4.1 KB]
    26 - Overfitting and Underfitting Definitions.html  [2.0 KB]
    17 - 6 Step Machine Learning Framework.mp4  [23.5 MB]
    21 - Features In Data.srt  [6.4 KB]
    24 - Modelling Tuning.srt  [4.8 KB]
    16 - Introducing Our Framework.mp4  [6.2 MB]
    22 - Modelling Splitting Data.mp4  [19.9 MB]
    23 - Modelling Picking the Model.mp4  [12.9 MB]
    29 - Optional Elements of AI.html  [975.0 B]
    22 - Modelling Splitting Data.srt  [7.3 KB]
    21 - Features In Data.mp4  [28.8 MB]
    17 - A 6 Step Field Guide for Machine Learning Modelling blog post.txt  [86.0 B]
    25 - Modelling Comparison.mp4  [26.8 MB]
    25 - Modelling Comparison.srt  [11.9 KB]
    15 - Section Overview.srt  [4.4 KB]
    27 - Experimentation.mp4  [18.7 MB]
    20 - Types of Evaluation.mp4  [9.6 MB]
    23 - Modelling Picking the Model.srt  [5.9 KB]
    24 - Modelling Tuning.mp4  [9.1 MB]
    27 - Experimentation.srt  [5.2 KB]
    18 - Types of Machine Learning Problems.mp4  [32.6 MB]
    19 - Types of Data.mp4  [33.2 MB]
    28 - Tools We Will Use.mp4  [20.4 MB]
    18 - Types of Machine Learning Problems.srt  [13.2 KB]
    19 - Types of Data.srt  [5.8 KB]
    15 - Section Overview.mp4  [9.5 MB]
    28 - Tools We Will Use.srt  [5.7 KB]
📁 17 - Learn Python
    291 - Expressions vs Statements.mp4  [4.8 MB]
    320 - Tuples 2.srt  [4.1 KB]
    301 - Booleans.srt  [4.3 KB]
    279 - Python 2 vs Python 3.srt  [7.9 KB]
    292 - Exercise Repl.txt  [55.0 B]
    309 - Python Keywords.txt  [56.0 B]
    278 - Latest Version Of Python.srt  [2.2 KB]
    275 - pythonorg.txt  [23.0 B]
    320 - Tuple Methods.txt  [53.0 B]
    293 - Strings.mp4  [21.1 MB]
    322 - Sets 2.srt  [11.2 KB]
    283 - How To Succeed.html  [280.0 B]
    314 - Dictionaries.mp4  [18.7 MB]
    322 - Sets 2.mp4  [70.8 MB]
    319 - Tuples.mp4  [15.1 MB]
    316 - Dictionary Keys.srt  [5.1 KB]
    275 - Python Interpreter.srt  [8.4 KB]
    321 - Sets.mp4  [39.0 MB]
    320 - Tuples 2.mp4  [11.6 MB]
    305 - Lists.mp4  [13.0 MB]
    296 - Escape Sequences.srt  [5.6 KB]
    280 - Exercise How Does Python Work.srt  [2.8 KB]
    309 - List Methods 2.srt  [5.9 KB]
    276 - How To Run Python Code.mp4  [72.4 MB]
    309 - Exercise Repl.txt  [33.0 B]
    303 - Python Comments Best Practices.txt  [45.0 B]
    293 - Strings.srt  [6.9 KB]
    296 - Escape Sequences.mp4  [12.9 MB]
    305 - Lists.srt  [6.5 KB]
    282 - Python Data Types.mp4  [19.2 MB]
    292 - Augmented Assignment Operator.mp4  [8.5 MB]
    289 - Optional bin and complex.mp4  [23.7 MB]
    299 - Immutability.mp4  [12.7 MB]
    290 - Variables.mp4  [99.5 MB]
    276 - Glotio.txt  [16.0 B]
    312 - List Unpacking.srt  [3.8 KB]
    282 - Python Data Types.srt  [5.9 KB]
    303 - DEVELOPER FUNDAMENTALS II.mp4  [39.5 MB]
    315 - DEVELOPER FUNDAMENTALS III.mp4  [14.9 MB]
    294 - String Concatenation.mp4  [3.8 MB]
    294 - String Concatenation.srt  [1.8 KB]
    288 - Exercise Operator Precedence.html  [683.0 B]
    289 - Base Numbers.txt  [50.0 B]
    315 - DEVELOPER FUNDAMENTALS III.srt  [3.5 KB]
    285 - Math Functions.mp4  [18.2 MB]
    291 - Expressions vs Statements.srt  [1.9 KB]
    275 - Python Interpreter.mp4  [138.0 MB]
    313 - None.srt  [2.2 KB]
    279 - Python 2 vs Python 3.mp4  [144.0 MB]
    278 - Latest Version Of Python.mp4  [12.9 MB]
    274 - What Is A Programming Language.mp4  [87.9 MB]
    297 - Formatted Strings.srt  [10.6 KB]
    312 - List Unpacking.mp4  [9.3 MB]
    276 - How To Run Python Code.srt  [6.4 KB]
    317 - Dictionary Methods.mp4  [15.0 MB]
    274 - What Is A Programming Language.srt  [7.4 KB]
    311 - Common List Patterns.srt  [7.2 KB]
    290 - Variables.srt  [16.2 KB]
    304 - Exercise Password Checker.mp4  [38.7 MB]
    284 - Numbers.mp4  [80.2 MB]
    287 - Exercise Repl.txt  [45.0 B]
    308 - List Methods.txt  [52.0 B]
    300 - BuiltIn Functions Methods.srt  [11.9 KB]
    280 - Exercise How Does Python Work.mp4  [28.8 MB]
    311 - Exercise Repl.txt  [33.0 B]
    300 - BuiltIn Functions Methods.mp4  [91.0 MB]
    313 - None.mp4  [4.5 MB]
    318 - Dictionary Methods 2.mp4  [46.3 MB]
    281 - Learning Python.srt  [2.5 KB]
    314 - Dictionaries.srt  [8.8 KB]
    301 - Booleans.mp4  [17.6 MB]
    310 - List Methods 3.srt  [6.4 KB]
    317 - Dictionary Methods.txt  [58.0 B]
    322 - Sets Methods.txt  [51.0 B]
    295 - Type Conversion.srt  [3.8 KB]
    299 - Immutability.srt  [3.8 KB]
    284 - Numbers.srt  [12.9 KB]
    279 - The Story of Python.txt  [43.0 B]
    288 - Exercise Repl.txt  [45.0 B]
    287 - Operator Precedence.mp4  [8.3 MB]
    277 - Our First Python Program.srt  [10.3 KB]
    290 - Python Keywords.txt  [56.0 B]
    319 - Tuples.srt  [6.4 KB]
    279 - Python 2 vs Python 3 another one.txt  [100.0 B]
    297 - Formatted Strings.mp4  [33.1 MB]
    289 - Optional bin and complex.srt  [5.1 KB]
    310 - List Methods 3.mp4  [29.5 MB]
    307 - Exercise Repl.txt  [32.0 B]
    281 - Learning Python.mp4  [12.1 MB]
    304 - Exercise Password Checker.srt  [8.7 KB]
    307 - Matrix.mp4  [12.9 MB]
    307 - Matrix.srt  [5.0 KB]
    318 - Exercise Repl.txt  [36.0 B]
    277 - Our First Python Program.mp4  [62.5 MB]
    309 - List Methods 2.mp4  [29.2 MB]
    286 - DEVELOPER FUNDAMENTALS I.mp4  [107.1 MB]
    308 - List Methods.srt  [13.4 KB]
    306 - List Slicing.srt  [9.8 KB]
    302 - Exercise Type Conversion.mp4  [39.0 MB]
    311 - Common List Patterns.mp4  [30.7 MB]
📁 5 - Data Science Environment Setup
    42 - Sharing your Conda Environment.html  [2.4 KB]
    44 - Jupyter Notebook Walkthrough 2.mp4  [56.6 MB]
    35 - What is Conda.srt  [3.4 KB]
    35 - Getting started with Conda documentation.txt  [78.0 B]
    33 - Section Overview.mp4  [3.9 MB]
    35 - Conda documentation.txt  [32.0 B]
    43 - Jupyter Notebook Walkthrough.srt  [15.4 KB]
    42 - Conda documentation on sharing an environment.txt  [111.0 B]
    35 - What is Conda.mp4  [7.3 MB]
    43 - Jupyter Notebook documentation.txt  [50.0 B]
    39 - Windows Environment Setup.mp4  [58.9 MB]
    39 - Miniconda download documentation.txt  [46.0 B]
    43 - Jupyter Notebook Walkthrough.mp4  [102.0 MB]
    37 - Mac Environment Setup.mp4  [261.4 MB]
    39 - Windows Environment Setup.srt  [7.4 KB]
    40 - Windows Environment Setup 2.mp4  [416.9 MB]
    40 - Windows Environment Setup 2.srt  [33.4 KB]
    37 - Miniconda download documentation.txt  [46.0 B]
    45 - Jupyter Notebook Walkthrough 3.srt  [11.5 KB]
    33 - Section Overview.srt  [2.0 KB]
    38 - Mac Environment Setup 2.mp4  [222.8 MB]
    45 - Jupyter Notebook Walkthrough 3.mp4  [127.5 MB]
    43 - Dataquest Jupyter Notebook for Beginners Tutorial.txt  [56.0 B]
    41 - Linux Environment Setup.html  [1.0 KB]
    37 - Mac Environment Setup.srt  [24.1 KB]
    36 - Conda Environments.srt  [5.7 KB]
    43 - 6-step-ml-framework.png  [324.2 KB]
    34 - Introducing Our Tools.srt  [4.2 KB]
    43 - heart-disease.csv  [11.1 KB]
    38 - Mac Environment Setup 2.srt  [22.0 KB]
    35 - conda-cheatsheet.pdf  [201.3 KB]
    44 - Jupyter Notebook Walkthrough 2.srt  [23.3 KB]
    36 - Conda Environments.mp4  [28.5 MB]
    35 - Getting your computer ready for machine learning How what and why you should use Anaconda Miniconda and Conda blog post.txt  [106.0 B]
📁 13 - Data Engineering
    196 - What Is Data.srt  [7.5 KB]
    200 - What Is A Data Engineer 4.mp4  [11.3 MB]
    197 - What Is A Data Engineer.srt  [5.0 KB]
    203 - Optional OLTP Databases.mp4  [47.5 MB]
    195 - Data Engineering Introduction.mp4  [9.6 MB]
    196 - What Is Data.mp4  [62.9 MB]
    197 - What Is A Data Engineer.mp4  [18.8 MB]
    201 - Types Of Databases.mp4  [41.7 MB]
    206 - Apache Spark and Apache Flink.srt  [2.3 KB]
    203 - Optional OLTP Databases.srt  [11.6 KB]
    198 - What Is A Data Engineer 2.srt  [6.4 KB]
    202 - Quick Note Upcoming Video.html  [481.0 B]
    200 - What Is A Data Engineer 4.srt  [3.8 KB]
    201 - A Primer on ACID Transactions.txt  [56.0 B]
    201 - Types Of Databases.srt  [8.1 KB]
    205 - Hadoop HDFS and MapReduce.srt  [5.1 KB]
    206 - Apache Spark and Apache Flink.mp4  [4.4 MB]
    207 - Kafka and Stream Processing.mp4  [22.9 MB]
    205 - Hadoop HDFS and MapReduce.mp4  [6.9 MB]
    195 - Data Engineering Introduction.srt  [4.2 KB]
    204 - Optional Learn SQL.html  [410.0 B]
    196 - Kaggle.txt  [31.0 B]
    199 - What Is A Data Engineer 3.mp4  [21.0 MB]
    207 - Kafka and Stream Processing.srt  [5.0 KB]
    199 - What Is A Data Engineer 3.srt  [5.1 KB]
    198 - What Is A Data Engineer 2.mp4  [24.2 MB]
    201 - OLTP vs OLAP.txt  [65.0 B]
📁 7 - NumPy
    73 - Sorting Arrays.mp4  [38.9 MB]
    72 - Comparison Operators.srt  [5.8 KB]
    69 - Reshape and Transpose.srt  [10.5 KB]
    65 - Viewing Arrays and Matrices.srt  [14.4 KB]
    74 - Turn Images Into NumPy Arrays.srt  [11.7 KB]
    74 - Introduction to NumPy Jupyter Notebook from the videos.txt  [129.0 B]
    60 - Introduction to NumPy Jupyter Notebook with annotations.txt  [123.0 B]
    65 - Viewing Arrays and Matrices.mp4  [81.8 MB]
    74 - Turn Images Into NumPy Arrays.mp4  [164.8 MB]
    63 - Creating NumPy Arrays.mp4  [97.7 MB]
    64 - NumPy Random Seed.srt  [10.8 KB]
    66 - Standard deviation and variance explained.txt  [55.0 B]
    70 - Dot Product vs Element Wise.mp4  [122.4 MB]
    68 - Standard Deviation and Variance.mp4  [61.5 MB]
    71 - Exercise Nut Butter Store Sales.srt  [18.9 KB]
    71 - Exercise Nut Butter Store Sales.mp4  [154.7 MB]
    74 - Introduction to NumPy Jupyter Notebook with annotations.txt  [123.0 B]
    73 - Sorting Arrays.srt  [10.4 KB]
    60 - NumPy Introduction.mp4  [21.3 MB]
    68 - Standard deviation and variance explained.txt  [55.0 B]
    60 - Introduction to NumPy Jupyter Notebook from the upcoming videos.txt  [129.0 B]
    63 - Creating NumPy Arrays.srt  [13.9 KB]
    62 - NumPy DataTypes and Attributes.srt  [20.3 KB]
    67 - Standard deviation and variance explained.txt  [55.0 B]
    60 - NumPy Introduction.srt  [7.3 KB]
    66 - Manipulating Arrays.srt  [17.3 KB]
    64 - NumPy Random Seed.mp4  [61.5 MB]
    69 - Reshape and Transpose.mp4  [91.3 MB]
    59 - Section Overview.srt  [2.9 KB]
    67 - Manipulating Arrays 2.mp4  [115.9 MB]
    60 - NumPy Documentation.txt  [22.0 B]
    75 - Exercise Imposter Syndrome.mp4  [53.7 MB]
    75 - Exercise Imposter Syndrome.srt  [4.2 KB]
    77 - Optional Extra NumPy resources.html  [1.0 KB]
    67 - Manipulating Arrays 2.srt  [12.0 KB]
    70 - Dot Product vs Element Wise.srt  [16.5 KB]
    59 - Section Overview.mp4  [22.4 MB]
    68 - Standard Deviation and Variance.srt  [9.7 KB]
    61 - Quick Note Correction In Next Video.html  [1.2 KB]
    76 - Assignment NumPy Practice.html  [2.2 KB]
    62 - NumPy DataTypes and Attributes.mp4  [113.6 MB]
    66 - Manipulating Arrays.mp4  [118.9 MB]
    72 - Comparison Operators.mp4  [38.2 MB]
    70 - Matrix Multiplication Explained.txt  [58.0 B]
    74 - numpy-images.zip  [7.3 MB]
📁 14 - Neural Networks Deep Learning Transfer Learning and TensorFlow 2
    232 - Building A Deep Learning Model.srt  [17.3 KB]
    249 - Submitting Model to Kaggle.srt  [19.4 KB]
    229 - Visualizing Our Data.mp4  [222.0 MB]
    233 - Building A Deep Learning Model 2.srt  [13.6 KB]
    225 - Documentation for loading images in TensorFlow.txt  [53.0 B]
    226 - Preprocess Images 2.srt  [14.7 KB]
    232 - Building A Deep Learning Model.mp4  [224.5 MB]
    233 - Keras in TensorFlow Overview Documentation.txt  [47.0 B]
    237 - Evaluating Our Model.srt  [12.2 KB]
    219 - Google Colab Example of GPU speed up versus CPU.txt  [53.0 B]
    237 - TensorBoard Callback Documentation.txt  [73.0 B]
    230 - Preparing Our Inputs and Outputs.srt  [8.1 KB]
    232 - PyTorch Hub PyTorch version of TensorFlow Hub.txt  [24.0 B]
    225 - TensorFlow guidelines for loading all kinds of data turning your data into Tensors.txt  [37.0 B]
    243 - Visualizing Model Predictions.srt  [20.3 KB]
    219 - Optional GPU and Google Colab.srt  [6.6 KB]
    213 - Kaggle Dog Breed Identification Competition Data.txt  [54.0 B]
    209 - Deep Learning and Unstructured Data.mp4  [119.8 MB]
    218 - Google Colab example GPU usage.txt  [53.0 B]
    238 - Early Stopping Callback a way to stop your model from training when it stops .txt  [75.0 B]
    216 - Importing TensorFlow 2.mp4  [210.6 MB]
    223 - Turning Data Labels Into Numbers.srt  [15.5 KB]
    242 - Transform Predictions To Text.srt  [20.4 KB]
    218 - Using A GPU.mp4  [146.3 MB]
    238 - Preventing Overfitting.srt  [5.8 KB]
    246 - Saving And Loading A Trained Model.mp4  [226.8 MB]
    237 - Evaluating Our Model.mp4  [116.0 MB]
    215 - Setting Up Our Data 2.mp4  [37.4 MB]
    232 - MobileNetV2 the model were using on TensorFlow Hub.txt  [71.0 B]
    208 - Section Overview.mp4  [15.1 MB]
    209 - Deep Learning and Unstructured Data.srt  [20.2 KB]
    228 - Turning Data Into Batches 2.srt  [22.8 KB]
    224 - Creating Our Own Validation Set.mp4  [94.8 MB]
    244 - Visualizing And Evaluate Model Predictions 2.srt  [21.0 KB]
    223 - Turning Data Labels Into Numbers.mp4  [195.7 MB]
    245 - Visualizing And Evaluate Model Predictions 3.mp4  [74.9 MB]
    213 - Uploading Project Data.mp4  [91.8 MB]
    225 - Preprocess Images.mp4  [158.1 MB]
    238 - Preventing Overfitting.mp4  [54.9 MB]
    251 - Finishing Dog Vision Where to next.html  [3.9 KB]
    229 - Visualizing Our Data.srt  [16.2 KB]
    224 - Creating Our Own Validation Set.srt  [11.4 KB]
    240 - Evaluating Performance With TensorBoard.srt  [10.9 KB]
    214 - Setting Up Our Data.mp4  [75.9 MB]
    236 - Summarizing Our Model.srt  [5.7 KB]
    248 - Making Predictions On Test Images.srt  [22.2 KB]
    247 - Training Model On Full Dataset.srt  [21.6 KB]
    228 - Turning Data Into Batches 2.mp4  [265.8 MB]
    249 - Submitting Model to Kaggle.mp4  [74.9 MB]
    211 - Kaggle Dog Breed Identification Competition the basis of our upcoming project.txt  [58.0 B]
    239 - Training Your Deep Neural Network.mp4  [297.2 MB]
    250 - Endtoend Dog Vision Notebook from the videos.txt  [130.0 B]
    212 - Google Colab Workspace.mp4  [58.5 MB]
    233 - Building A Deep Learning Model 2.mp4  [192.2 MB]
    222 - Preparing The Images.srt  [16.4 KB]
    211 - Setting Up Google Colab.mp4  [80.3 MB]
    241 - Make And Transform Predictions.srt  [21.4 KB]
    214 - Setting Up Our Data.srt  [6.9 KB]
    213 - Google Colab IO example how to get data in and out of your Colab notebook.txt  [52.0 B]
    248 - Dog Vision Prediction Probabilities Array.txt  [109.0 B]
    242 - Transform Predictions To Text.mp4  [228.5 MB]
    227 - Turning Data Into Batches.mp4  [155.3 MB]
    249 - Dog Vision Predictions with MobileNetV2 Ready for Kaggle Submission.txt  [119.0 B]
    219 - Optional GPU and Google Colab.mp4  [69.1 MB]
    212 - Google Colab FAQ things you should know about Google Colab.txt  [49.0 B]
    218 - Using A GPU.srt  [13.6 KB]
    222 - Preparing The Images.mp4  [243.6 MB]
    250 - Making Predictions On Our Images.srt  [22.1 KB]
    241 - Make And Transform Predictions.mp4  [279.1 MB]
    211 - Google Colab IO example how to get data in and out of your Colab notebook.txt  [52.0 B]
    217 - Optional TensorFlow 20 Default Issue.mp4  [35.0 MB]
    220 - Optional Reloading Colab Notebook.srt  [9.2 KB]
    232 - TensorFlow Hub resource for pretrained deep learning models and more.txt  [18.0 B]
    219 - Introduction to Google Colab example notebook.txt  [55.0 B]
    225 - Preprocess Images.srt  [14.2 KB]
    235 - Building A Deep Learning Model 4.mp4  [155.1 MB]
    250 - Making Predictions On Our Images.mp4  [119.4 MB]
    245 - Visualizing And Evaluate Model Predictions 3.srt  [15.9 KB]
    234 - Building A Deep Learning Model 3.srt  [12.2 KB]
    242 - TensorFlow documentation for the unbatch function.txt  [66.0 B]
    221 - Loading Our Data Labels.mp4  [205.9 MB]
    211 - Google Colab our workspace for the upcoming project.txt  [34.0 B]
    230 - Preparing Our Inputs and Outputs.mp4  [84.7 MB]
    216 - Importing TensorFlow 2.srt  [19.2 KB]
    211 - Setting Up Google Colab.srt  [10.5 KB]
    226 - Preprocess Images 2.mp4  [190.4 MB]
    215 - Setting Up Our Data 2.srt  [2.2 KB]
    236 - Summarizing Our Model.mp4  [82.0 MB]
    239 - Training Your Deep Neural Network.srt  [25.8 KB]
    210 - Setting Up With Google.html  [568.0 B]
    228 - Yann LeCuns OG of deep learning Tweet on Batch Sizes.txt  [57.0 B]
    211 - Introduction to Google Colab example notebook.txt  [55.0 B]
    220 - Optional Reloading Colab Notebook.mp4  [167.0 MB]
    208 - Section Overview.srt  [2.7 KB]
    232 - Andrei Karpathys talk on AI at Tesla.txt  [34.0 B]
    234 - Building A Deep Learning Model 3.mp4  [197.6 MB]
    246 - Saving And Loading A Trained Model.srt  [19.5 KB]
    221 - Loading Our Data Labels.srt  [17.7 KB]
    247 - Training Model On Full Dataset.mp4  [80.9 MB]
    224 - Blog post by Rachel Thomas of fastai on how and why you should create a validation set.txt  [47.0 B]
📁 16 - Career Advice Extra Bits
    262 - What If I Dont Have Enough Experience.mp4  [312.1 MB]
    266 - JTS Start With Why.srt  [3.0 KB]
    265 - JTS Learn to Learn.srt  [2.3 KB]
    262 - What If I Dont Have Enough Experience.srt  [19.2 KB]
    261 - Quick Note Upcoming Video.html  [587.0 B]
    260 - Endorsements On LinkedIn.html  [1.4 KB]
    269 - CWD Git Github 2.srt  [21.5 KB]
    271 - Contributing To Open Source 2.mp4  [213.7 MB]
    273 - Coding Challenges.html  [948.0 B]
    269 - CWD Git Github 2.mp4  [228.7 MB]
    268 - CWD Git Github.srt  [21.7 KB]
    266 - JTS Start With Why.mp4  [14.3 MB]
    271 - Contributing To Open Source 2.srt  [11.5 KB]
    270 - Contributing To Open Source.mp4  [235.6 MB]
    268 - CWD Git Github.mp4  [362.0 MB]
    263 - Learning Guideline.html  [336.0 B]
    267 - Quick Note Upcoming Videos.html  [352.0 B]
    272 - Exercise Contribute To Open Source.html  [1.9 KB]
    265 - JTS Learn to Learn.mp4  [10.4 MB]
    270 - Contributing To Open Source.srt  [17.6 KB]
    264 - Quick Note Upcoming Videos.html  [565.0 B]
📁 18 - Learn Python Part 2
    365 - Solution Repl.txt  [41.0 B]
    363 - List Comprehensions.mp4  [38.9 MB]
    337 - While Loops.srt  [8.4 KB]
    332 - For Loops.srt  [8.9 KB]
    337 - While Loops.mp4  [21.0 MB]
    332 - For Loops.mp4  [25.2 MB]
    330 - Exercise Logical Operators.mp4  [37.0 MB]
    354 - Scope Rules.mp4  [29.3 MB]
    345 - Default Parameters and Keyword Arguments.srt  [6.3 KB]
    358 - Pure Functions.mp4  [60.3 MB]
    328 - Short Circuiting.mp4  [12.2 MB]
    338 - While Loops 2.srt  [7.3 KB]
    371 - Different Ways To Import.mp4  [39.0 MB]
    343 - Functions.srt  [10.0 KB]
    370 - Packages in Python.srt  [13.9 KB]
    336 - enumerate.mp4  [17.7 MB]
    358 - Pure Functions.srt  [11.0 KB]
    352 - Exercise Functions.mp4  [16.4 MB]
    364 - Set Comprehensions.mp4  [26.6 MB]
    371 - Different Ways To Import.srt  [8.3 KB]
    334 - Exercise Tricky Counter.srt  [3.9 KB]
    334 - Solution Repl.txt  [31.0 B]
    361 - zip.mp4  [16.0 MB]
    340 - Our First GUI.mp4  [79.5 MB]
    330 - Exercise Logical Operators.srt  [9.6 KB]
    356 - Solution Repl.txt  [34.0 B]
    363 - List Comprehensions.srt  [10.6 KB]
    350 - Clean Code.mp4  [13.0 MB]
    342 - Exercise Find Duplicates.srt  [4.8 KB]
    350 - Clean Code.srt  [6.0 KB]
    339 - break continue pass.mp4  [14.1 MB]
    336 - enumerate.srt  [5.0 KB]
    351 - args and kwargs.srt  [9.0 KB]
    354 - Scope Rules.srt  [9.0 KB]
    367 - Modules in Python.srt  [13.7 KB]
    349 - Docstrings.srt  [4.4 KB]
    329 - Logical Operators.srt  [10.1 KB]
    340 - Our First GUI.srt  [11.5 KB]
    367 - Modules in Python.mp4  [168.4 MB]
    356 - nonlocal Keyword.mp4  [14.5 MB]
    373 - Bonus Resource Python Cheatsheet.html  [489.0 B]
    324 - Conditional Logic.srt  [18.5 KB]
    326 - Truthy vs Falsey.mp4  [73.7 MB]
    331 - is vs.mp4  [30.8 MB]
    325 - Indentation In Python.srt  [5.5 KB]
    365 - Exercise Comprehensions.mp4  [14.6 MB]
    366 - Python Exam Testing Your Understanding.html  [1.1 KB]
    340 - Exercise Repl.txt  [38.0 B]
    369 - Optional PyCharm.srt  [11.4 KB]
    355 - global Keyword.srt  [7.3 KB]
    359 - map.mp4  [48.3 MB]
    353 - Scope.srt  [4.7 KB]
    327 - Ternary Operator.mp4  [12.5 MB]
    323 - Breaking The Flow.srt  [2.8 KB]
    333 - Iterables.mp4  [54.3 MB]
    364 - Set Comprehensions.srt  [7.6 KB]
    351 - args and kwargs.mp4  [33.1 MB]
    346 - return.srt  [16.2 KB]
    360 - filter.mp4  [15.0 MB]
    359 - map.srt  [7.2 KB]
    327 - Ternary Operator.srt  [5.4 KB]
    365 - Exercise Comprehensions.srt  [5.7 KB]
    323 - Breaking The Flow.mp4  [12.7 MB]
    329 - Logical Operators.mp4  [25.4 MB]
    345 - Default Parameters and Keyword Arguments.mp4  [29.1 MB]
    328 - Short Circuiting.srt  [4.8 KB]
    361 - zip.srt  [4.2 KB]
    344 - Parameters and Arguments.srt  [5.5 KB]
    339 - break continue pass.srt  [5.6 KB]
    346 - return.mp4  [56.7 MB]
    348 - Methods vs Functions.srt  [6.0 KB]
    325 - Indentation In Python.mp4  [22.0 MB]
    335 - range.mp4  [34.3 MB]
    341 - DEVELOPER FUNDAMENTALS IV.mp4  [41.3 MB]
    326 - Truthy vs Falsey Stackoverflow.txt  [109.0 B]
    326 - Truthy vs Falsey.srt  [6.3 KB]
    355 - global Keyword.mp4  [33.4 MB]
    324 - Conditional Logic.mp4  [92.5 MB]
    334 - Exercise Tricky Counter.mp4  [14.1 MB]
    372 - Next Steps.html  [959.0 B]
    360 - filter.srt  [5.9 KB]
    362 - reduce.mp4  [65.8 MB]
    357 - Why Do We Need Scope.mp4  [16.1 MB]
    353 - Scope.mp4  [12.5 MB]
    343 - Functions.mp4  [34.1 MB]
    349 - Docstrings.mp4  [15.7 MB]
    356 - nonlocal Keyword.srt  [4.0 KB]
    348 - Methods vs Functions.mp4  [37.6 MB]
    333 - Iterables.srt  [8.1 KB]
    347 - Exercise Tesla.html  [402.0 B]
    340 - Solution Repl.txt  [38.0 B]
    344 - Parameters and Arguments.mp4  [17.5 MB]
    368 - Quick Note Upcoming Videos.html  [448.0 B]
    335 - range.srt  [6.8 KB]
    369 - Optional PyCharm.mp4  [65.2 MB]
    352 - Exercise Functions.srt  [5.4 KB]
    342 - Exercise Find Duplicates.mp4  [15.8 MB]
    341 - DEVELOPER FUNDAMENTALS IV.srt  [7.9 KB]
    331 - is vs.srt  [10.0 KB]
    362 - reduce.srt  [8.5 KB]
📁 10 - Supervised Learning Classification Regression
    150 - Milestone Projects.html  [738.0 B]
📁 1 - Introduction
    1 - Course Outline.srt  [8.3 KB]
📁 20 - Where To Go From Here
    376 - Thank You.srt  [3.9 KB]
    377 - Thank You Part 2.html  [730.0 B]
    375 - Become An Alumni.html  [944.0 B]
    376 - Thank You.mp4  [15.4 MB]
📁 4 - The 2 Paths
    30 - The 2 Paths.srt  [4.4 KB]
    30 - The 2 Paths.mp4  [6.8 MB]
    31 - Python Machine Learning Monthly.html  [917.0 B]
    32 - Endorsements On LinkedIN.html  [1.4 KB]