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  • TA的每日心情
    qdsmile擦汗
    2023-5-17 08:49
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    发表于 2024-5-19 02:55:00 | 显示全部楼层 |阅读模式
    ├─1-Introduction
    │        1-Course Outline.mp4
    │        1-Course Outline.srt
    │        2-Join Our Online Classroom.mp4
    │        2-Join Our Online Classroom.srt
    │        3-Exercise Meet Your Classmates and Instructor.html
    │        4-Your First Day.srt
    │       
    ├─2-Machine Learning 101
    │        5-What Is Machine Learning.mp4
    │        5-What Is Machine Learning.srt
    │        6-AIMachine LearningData Science.mp4
    │        6-AIMachine LearningData Science.srt
    │        7-Exercise Machine Learning Playground.mp4
    │        7-Exercise Machine Learning Playground.srt
    │        7-Teachable Machine.txt
    │        8-How Did We Get Here.mp4
    │        8-How Did We Get Here.srt
    │        9-Exercise YouTube Recommendation Engine.mp4
    │        9-Exercise YouTube Recommendation Engine.srt
    │        9-Machine Learning Playground.txt
    │        10-Types of Machine Learning.mp4
    │        10-Types of Machine Learning.srt
    │        11-Are You Getting It Yet.html
    │        12-What Is Machine Learning Round 2.mp4
    │        12-What Is Machine Learning Round 2.srt
    │        13-Section Review.mp4
    │        13-Section Review.srt
    │        14-Monthly Coding Challenges Free Resources and Guides.html
    │       
    ├─3-Machine Learning and Data Science Framework
    │        15-Section Overview.mp4
    │        15-Section Overview.srt
    │        16-Introducing Our Framework.mp4
    │        16-Introducing Our Framework.srt
    │        17-6 Step Machine Learning Framework.mp4
    │        17-A 6 Step Field Guide for Machine Learning Modelling blog post.txt
    │        18-Types of Machine Learning Problems.mp4
    │        18-Types of Machine Learning Problems.srt
    │        19-Types of Data.mp4
    │        19-Types of Data.srt
    │        20-Types of Evaluation.mp4
    │        20-Types of Evaluation.srt
    │        21-Features In Data.mp4
    │        21-Features In Data.srt
    │        22-Modelling Splitting Data.mp4
    │        22-Modelling Splitting Data.srt
    │        23-Modelling Picking the Model.mp4
    │        23-Modelling Picking the Model.srt
    │        24-Modelling Tuning.mp4
    │        24-Modelling Tuning.srt
    │        25-Modelling Comparison.mp4
    │        25-Modelling Comparison.srt
    │        26-Overfitting and Underfitting Definitions.html
    │        27-Experimentation.mp4
    │        27-Experimentation.srt
    │        28-Tools We Will Use.mp4
    │        28-Tools We Will Use.srt
    │        29-Optional Elements of AI.html
    │       
    ├─4-The 2 Paths
    │        30-The 2 Paths.mp4
    │        30-The 2 Paths.srt
    │        31-Python Machine Learning Monthly.html
    │        32-Endorsements On LinkedIN.html
    │       
    ├─5-Data Science Environment Setup
    │        33-Section Overview.mp4
    │        33-Section Overview.srt
    │        34-Introducing Our Tools.srt
    │        35-Conda documentation.txt
    │        35-conda-cheatsheet.pdf
    │        35-Getting started with Conda documentation.txt
    │        35-Getting your computer ready for machine learning How what and why you should use Anaconda Miniconda and Conda blog post.txt
    │        35-What is Conda.mp4
    │        35-What is Conda.srt
    │        36-Conda Environments.mp4
    │        36-Conda Environments.srt
    │        37-Mac Environment Setup.mp4
    │        37-Mac Environment Setup.srt
    │        37-Miniconda download documentation.txt
    │        38-Mac Environment Setup 2.mp4
    │        38-Mac Environment Setup 2.srt
    │        39-Miniconda download documentation.txt
    │        39-Windows Environment Setup.mp4
    │        39-Windows Environment Setup.srt
    │        40-Windows Environment Setup 2.mp4
    │        40-Windows Environment Setup 2.srt
    │        41-Linux Environment Setup.html
    │        42-Conda documentation on sharing an environment.txt
    │        42-Sharing your Conda Environment.html
    │        43-6-step-ml-framework.png
    │        43-Dataquest Jupyter Notebook for Beginners Tutorial.txt
    │        43-Jupyter Notebook documentation.txt
    │        43-Jupyter Notebook Walkthrough.mp4
    │        43-Jupyter Notebook Walkthrough.srt
    │        44-Jupyter Notebook Walkthrough 2.mp4
    │        44-Jupyter Notebook Walkthrough 2.srt
    │        45-Jupyter Notebook Walkthrough 3.mp4
    │        45-Jupyter Notebook Walkthrough 3.srt
    │       
    ├─6-Pandas Data Analysis
    │        46-Section Overview.mp4
    │        46-Section Overview.srt
    │        47-Downloading Workbooks and Assignments.html
    │        48-10 minutes to pandas from the documentation.txt
    │        48-Introduction to Pandas Jupyter Notebook from the upcoming videos.txt
    │        48-Introduction to Pandas Jupyter Notebook with annotations.txt
    │        48-Pandas Documentation.txt
    │        48-Pandas Introduction.mp4
    │        48-Pandas Introduction.srt
    │        49-pandas-anatomy-of-a-dataframe.png
    │        49-Series Data Frames and CSVs.mp4
    │        49-Series Data Frames and CSVs.srt
    │        50-Data from URLs.html
    │        51-Describing Data with Pandas.mp4
    │        51-Describing Data with Pandas.srt
    │        52-Selecting and Viewing Data with Pandas.mp4
    │        52-Selecting and Viewing Data with Pandas.srt
    │        53-Selecting and Viewing Data with Pandas Part 2.mp4
    │        53-Selecting and Viewing Data with Pandas Part 2.srt
    │        54-Jake VanderPlass Data Manipulation with Pandas.txt
    │        54-Manipulating Data.mp4
    │        54-Manipulating Data.srt
    │        55-Manipulating Data 2.mp4
    │        55-Manipulating Data 2.srt
    │        55-pandas-anatomy-of-a-dataframe.png
    │        56-Introduction to Pandas Jupyter Notebook from the videos.txt
    │        56-Introduction to Pandas Jupyter Notebook with annotations.txt
    │        56-Manipulating Data 3.mp4
    │        56-Manipulating Data 3.srt
    │        57-Assignment Pandas Practice.html
    │        58-Course notebooks Github.txt
    │        58-Google Colab.txt
    │        58-How To Download The Course Assignments.mp4
    │        58-How To Download The Course Assignments.srt
    │       
    ├─7-NumPy
    │        59-Section Overview.mp4
    │        59-Section Overview.srt
    │        60-Introduction to NumPy Jupyter Notebook from the upcoming videos.txt
    │        60-Introduction to NumPy Jupyter Notebook with annotations.txt
    │        60-NumPy Documentation.txt
    │        60-NumPy Introduction.mp4
    │        60-NumPy Introduction.srt
    │        61-Quick Note Correction In Next Video.html
    │        62-NumPy DataTypes and Attributes.mp4
    │        62-NumPy DataTypes and Attributes.srt
    │        63-Creating NumPy Arrays.mp4
    │        63-Creating NumPy Arrays.srt
    │        64-NumPy Random Seed.mp4
    │        64-NumPy Random Seed.srt
    │        65-Viewing Arrays and Matrices.mp4
    │        65-Viewing Arrays and Matrices.srt
    │        66-Manipulating Arrays.mp4
    │        66-Manipulating Arrays.srt
    │        66-Standard deviation and variance explained.txt
    │        67-Manipulating Arrays 2.mp4
    │        67-Manipulating Arrays 2.srt
    │        67-Standard deviation and variance explained.txt
    │        68-Standard deviation and variance explained.txt
    │        68-Standard Deviation and Variance.mp4
    │        68-Standard Deviation and Variance.srt
    │        69-Reshape and Transpose.mp4
    │        69-Reshape and Transpose.srt
    │        70-Dot Product vs Element Wise.mp4
    │        70-Dot Product vs Element Wise.srt
    │        70-Matrix Multiplication Explained.txt
    │        71-Exercise Nut Butter Store Sales.mp4
    │        71-Exercise Nut Butter Store Sales.srt
    │        72-Comparison Operators.mp4
    │        72-Comparison Operators.srt
    │        73-Sorting Arrays.mp4
    │        73-Sorting Arrays.srt
    │        74-Introduction to NumPy Jupyter Notebook from the videos.txt
    │        74-Introduction to NumPy Jupyter Notebook with annotations.txt
    │        74-Turn Images Into NumPy Arrays.mp4
    │        74-Turn Images Into NumPy Arrays.srt
    │        75-Exercise Imposter Syndrome.mp4
    │        75-Exercise Imposter Syndrome.srt
    │        76-Assignment NumPy Practice.html
    │        77-Optional Extra NumPy resources.html
    │       
    ├─8-Matplotlib Plotting and Data Visualization
    │        78-Section Overview.mp4
    │        78-Section Overview.srt
    │        79-Introduction to Matplotlib Jupyter Notebook from the upcoming videos.txt
    │        79-Matplotlib Documentation.txt
    │        79-Matplotlib Introduction.mp4
    │        79-Matplotlib Introduction.srt
    │        80-Importing And Using Matplotlib.mp4
    │        80-Importing And Using Matplotlib.srt
    │        81-Anatomy Of A Matplotlib Figure.mp4
    │        81-Anatomy Of A Matplotlib Figure.srt
    │        81-matplotlib-anatomy-of-a-plot-with-code.png
    │        81-matplotlib-anatomy-of-a-plot.png
    │        82-Scatter Plot And Bar Plot.mp4
    │        82-Scatter Plot And Bar Plot.srt
    │        83-Histograms And Subplots.mp4
    │        83-Histograms And Subplots.srt
    │        84-Subplots Option 2.mp4
    │        84-Subplots Option 2.srt
    │        85-Quick Tip Data Visualizations.mp4
    │        85-Quick Tip Data Visualizations.srt
    │        86-Plotting From Pandas DataFrames.mp4
    │        86-Plotting From Pandas DataFrames.srt
    │        87-Quick Note Regular Expressions.html
    │        88-Plotting From Pandas DataFrames 2.mp4
    │        88-Plotting From Pandas DataFrames 2.srt
    │        89-Plotting from Pandas DataFrames 3.mp4
    │        89-Plotting from Pandas DataFrames 3.srt
    │        90-Plotting from Pandas DataFrames 4.mp4
    │        90-Plotting from Pandas DataFrames 4.srt
    │        91-Plotting from Pandas DataFrames 5.mp4
    │        91-Plotting from Pandas DataFrames 5.srt
    │        92-Plotting from Pandas DataFrames 6.mp4
    │        92-Plotting from Pandas DataFrames 6.srt
    │        93-Plotting from Pandas DataFrames 7.mp4
    │        93-Plotting from Pandas DataFrames 7.srt
    │        94-Customizing Your Plots.mp4
    │        94-Customizing Your Plots.srt
    │        95-Customizing Your Plots 2.mp4
    │        95-Customizing Your Plots 2.srt
    │        96-Introduction to Matplotlib Notebook from the videos.txt
    │        96-Saving And Sharing Your Plots.mp4
    │        96-Saving And Sharing Your Plots.srt
    │        97-Assignment Matplotlib Practice.html
    │       
    ├─9-Scikitlearn Creating Machine Learning Models
    │        98-Section Overview.mp4
    │        98-Section Overview.srt
    │        99-Introduction to ScikitLearn Jupyter Notebook from the upcoming videos.txt
    │        99-Introduction to ScikitLearn Jupyter Notebook with annotations.txt
    │        99-ScikitLearn Documentation.txt
    │        99-Scikitlearn Introduction.mp4
    │        99-Scikitlearn Introduction.srt
    │        100-Quick Note Upcoming Video.html
    │        101-Refresher What Is Machine Learning.mp4
    │        101-Refresher What Is Machine Learning.srt
    │        102-Quick Note Upcoming Videos.html
    │        103-Scikitlearn Cheatsheet.mp4
    │        103-Scikitlearn Cheatsheet.srt
    │        103-ScikitLearn Reference Notebook.txt
    │        104-Example ScikitLearn Workflow Notebook.txt
    │        104-Typical scikitlearn Workflow.mp4
    │        104-Typical scikitlearn Workflow.srt
    │        105-Optional Debugging Warnings In Jupyter.mp4
    │        105-Optional Debugging Warnings In Jupyter.srt
    │        106-Getting Your Data Ready Splitting Your Data.mp4
    │        106-Getting Your Data Ready Splitting Your Data.srt
    │        107-Quick Tip Clean Transform Reduce.mp4
    │        107-Quick Tip Clean Transform Reduce.srt
    │        108-Getting Your Data Ready Convert Data To Numbers.mp4
    │        108-Getting Your Data Ready Convert Data To Numbers.srt
    │        109-Note Update to next video OneHotEncoder can handle NaNNone values.html
    │        110-Getting Your Data Ready Handling Missing Values With Pandas.mp4
    │        110-Getting Your Data Ready Handling Missing Values With Pandas.srt
    │        111-Extension Feature Scaling.html
    │        112-Note Correction in the upcoming video splitting data.html
    │        113-Getting Your Data Ready Handling Missing Values With Scikitlearn.mp4
    │        113-Getting Your Data Ready Handling Missing Values With Scikitlearn.srt
    │        114-NEW Choosing The Right Model For Your Data.mp4
    │        114-NEW Choosing The Right Model For Your Data.srt
    │        115-NEW Choosing The Right Model For Your Data 2 Regression.mp4
    │        115-NEW Choosing The Right Model For Your Data 2 Regression.srt
    │        116-Quick Note Decision Trees.html
    │        117-Quick Tip How ML Algorithms Work.mp4
    │        117-Quick Tip How ML Algorithms Work.srt
    │        118-Choosing The Right Model For Your Data 3 Classification.mp4
    │        118-Choosing The Right Model For Your Data 3 Classification.srt
    │        119-Fitting A Model To The Data.mp4
    │        119-Fitting A Model To The Data.srt
    │        120-Making Predictions With Our Model.mp4
    │        120-Making Predictions With Our Model.srt
    │        121-predict vs predictproba.mp4
    │        121-predict vs predictproba.srt
    │        122-NEW Making Predictions With Our Model Regression.mp4
    │        122-NEW Making Predictions With Our Model Regression.srt
    │        123-NEW Evaluating A Machine Learning Model Score Part 1.mp4
    │        123-NEW Evaluating A Machine Learning Model Score Part 1.srt
    │        124-NEW Evaluating A Machine Learning Model Score Part 2.mp4
    │        124-NEW Evaluating A Machine Learning Model Score Part 2.srt
    │        125-Evaluating A Machine Learning Model 2 Cross Validation.mp4
    │        125-Evaluating A Machine Learning Model 2 Cross Validation.srt
    │        126-Evaluating A Classification Model 1 Accuracy.mp4
    │        126-Evaluating A Classification Model 1 Accuracy.srt
    │        127-Evaluating A Classification Model 2 ROC Curve.mp4
    │        127-Evaluating A Classification Model 2 ROC Curve.srt
    │        128-Evaluating A Classification Model 3 ROC Curve.mp4
    │        128-Evaluating A Classification Model 3 ROC Curve.srt
    │        129-Reading Extension ROC Curve AUC.html
    │        130-Evaluating A Classification Model 4 Confusion Matrix.mp4
    │        130-Evaluating A Classification Model 4 Confusion Matrix.srt
    │        130-Notebook from video with updated confusion matrix labels.txt
    │        131-NEW Evaluating A Classification Model 5 Confusion Matrix.mp4
    │        131-NEW Evaluating A Classification Model 5 Confusion Matrix.srt
    │        132-Evaluating A Classification Model 6 Classification Report.mp4
    │        132-Evaluating A Classification Model 6 Classification Report.srt
    │        133-NEW Evaluating A Regression Model 1 R2 Score.mp4
    │        133-NEW Evaluating A Regression Model 1 R2 Score.srt
    │        134-NEW Evaluating A Regression Model 2 MAE.mp4
    │        134-NEW Evaluating A Regression Model 2 MAE.srt
    │        135-NEW Evaluating A Regression Model 3 MSE.mp4
    │        135-NEW Evaluating A Regression Model 3 MSE.srt
    │        136-Machine Learning Model Evaluation.html
    │        137-NEW Evaluating A Model With Cross Validation and Scoring Parameter.mp4
    │        137-NEW Evaluating A Model With Cross Validation and Scoring Parameter.srt
    │        138-NEW Evaluating A Model With Scikitlearn Functions.mp4
    │        138-NEW Evaluating A Model With Scikitlearn Functions.srt
    │        139-Improving A Machine Learning Model.mp4
    │        139-Improving A Machine Learning Model.srt
    │        140-Tuning Hyperparameters.mp4
    │        140-Tuning Hyperparameters.srt
    │        141-Tuning Hyperparameters 2.mp4
    │        141-Tuning Hyperparameters 2.srt
    │        142-Tuning Hyperparameters 3.mp4
    │        142-Tuning Hyperparameters 3.srt
    │        143-Note Metric Comparison Improvement.html
    │        144-Quick Tip Correlation Analysis.mp4
    │        144-Quick Tip Correlation Analysis.srt
    │        145-Saving And Loading A Model.mp4
    │        145-Saving And Loading A Model.srt
    │        146-Saving And Loading A Model 2.mp4
    │        146-Saving And Loading A Model 2.srt
    │        147-Putting It All Together.mp4
    │        147-Putting It All Together.srt
    │        147-Reading extension ScikitLearns Pipeline class explained.txt
    │        148-Introduction to ScikitLearn Jupyter Notebook from the videos.txt
    │        148-Introduction to ScikitLearn Jupyter Notebook with annotations.txt
    │        148-Putting It All Together 2.mp4
    │        148-Putting It All Together 2.srt
    │        149-ScikitLearn Practice.html
    │       
    ├─10-Supervised Learning Classification Regression
    │        150-Milestone Projects.html
    │       
    ├─11-Milestone Project 1 Supervised Learning Classification
    │        151-Section Overview.mp4
    │        151-Section Overview.srt
    │        152-Endtoend Heart Disease Classification Notebook same as in videos.txt
    │        152-Endtoend Heart Disease Classification Notebook with annotations.txt
    │        152-Project Overview.mp4
    │        152-Project Overview.srt
    │        152-Structured Data Projects on GitHub.txt
    │        153-Project Environment Setup.mp4
    │        153-Project Environment Setup.srt
    │        154-Optional Windows Project Environment Setup.mp4
    │        154-Optional Windows Project Environment Setup.srt
    │        155-Step 14 Framework Setup.mp4
    │        155-Step 14 Framework Setup.srt
    │        156-Getting Our Tools Ready.mp4
    │        156-Getting Our Tools Ready.srt
    │        157-Exploring Our Data.mp4
    │        157-Exploring Our Data.srt
    │        158-Finding Patterns.mp4
    │        158-Finding Patterns.srt
    │        159-Finding Patterns 2.mp4
    │        159-Finding Patterns 2.srt
    │        160-Finding Patterns 3.mp4
    │        160-Finding Patterns 3.srt
    │        161-Preparing Our Data For Machine Learning.mp4
    │        161-Preparing Our Data For Machine Learning.srt
    │        162-Choosing The Right Models.mp4
    │        162-Choosing The Right Models.srt
    │        163-Experimenting With Machine Learning Models.mp4
    │        163-Experimenting With Machine Learning Models.srt
    │        164-TuningImproving Our Model.mp4
    │        164-TuningImproving Our Model.srt
    │        165-Tuning Hyperparameters.mp4
    │        165-Tuning Hyperparameters.srt
    │        166-Tuning Hyperparameters 2.mp4
    │        166-Tuning Hyperparameters 2.srt
    │        167-Tuning Hyperparameters 3.mp4
    │        167-Tuning Hyperparameters 3.srt
    │        168-Quick Note Confusion Matrix Labels.html
    │        169-Evaluating Our Model.mp4
    │        169-Evaluating Our Model.srt
    │        170-Evaluating Our Model 2.mp4
    │        170-Evaluating Our Model 2.srt
    │        171-Evaluating Our Model 3.mp4
    │        171-Evaluating Our Model 3.srt
    │        172-Finding The Most Important Features.mp4
    │        172-Finding The Most Important Features.srt
    │        173-Endtoend Heart Disease Classification Notebook same as in videos.txt
    │        173-Endtoend Heart Disease Classification Notebook with annotations.txt
    │        173-Reviewing The Project.mp4
    │        173-Reviewing The Project.srt
    │       
    ├─12-Milestone Project 2 Supervised Learning Time Series Data
    │        174-Section Overview.mp4
    │        174-Section Overview.srt
    │        175-Endtoend Bluebook Bulldozer Regression Notebook same as in videos.txt
    │        175-Endtoend Bluebook Bulldozer Regression Notebook with annotations.txt
    │        175-Kaggle Bluebook for Bulldozers Competition.txt
    │        175-Project Overview.mp4
    │        175-Project Overview.srt
    │        175-Structured Data Projects on GitHub.txt
    │        176-Downloading the data for the next two projects.html
    │        177-Project Environment Setup.mp4
    │        177-Project Environment Setup.srt
    │        178-Step 14 Framework Setup.mp4
    │        178-Step 14 Framework Setup.srt
    │        179-Exploring Our Data.mp4
    │        179-Exploring Our Data.srt
    │        180-Exploring Our Data 2.mp4
    │        180-Exploring Our Data 2.srt
    │        181-Feature Engineering.mp4
    │        181-Feature Engineering.srt
    │        182-Turning Data Into Numbers.mp4
    │        182-Turning Data Into Numbers.srt
    │        183-Filling Missing Numerical Values.mp4
    │        183-Filling Missing Numerical Values.srt
    │        183-Pandas Categorical Datatype Documentation.txt
    │        184-Filling Missing Categorical Values.mp4
    │        184-Filling Missing Categorical Values.srt
    │        185-Fitting A Machine Learning Model.mp4
    │        185-Fitting A Machine Learning Model.srt
    │        186-Splitting Data.mp4
    │        186-Splitting Data.srt
    │        187-Challenge Whats wrong with splitting data after filling it.html
    │        188-Custom Evaluation Function.mp4
    │        188-Custom Evaluation Function.srt
    │        189-Reducing Data.mp4
    │        189-Reducing Data.srt
    │        190-RandomizedSearchCV.mp4
    │        190-RandomizedSearchCV.srt
    │        191-Improving Hyperparameters.mp4
    │        191-Improving Hyperparameters.srt
    │        192-Preproccessing Our Data.mp4
    │        192-Preproccessing Our Data.srt
    │        193-Making Predictions.mp4
    │        193-Making Predictions.srt
    │        194-Endtoend Bluebook Bulldozer Regression Notebook same as in videos.txt
    │        194-Endtoend Bluebook Bulldozer Regression Notebook with annotations.txt
    │        194-Feature Importance.mp4
    │        194-Feature Importance.srt
    │       
    ├─13-Data Engineering
    │        195-Data Engineering Introduction.mp4
    │        195-Data Engineering Introduction.srt
    │        196-Kaggle.txt
    │        196-What Is Data.mp4
    │        196-What Is Data.srt
    │        197-What Is A Data Engineer.mp4
    │        197-What Is A Data Engineer.srt
    │        198-What Is A Data Engineer 2.mp4
    │        198-What Is A Data Engineer 2.srt
    │        199-What Is A Data Engineer 3.mp4
    │        199-What Is A Data Engineer 3.srt
    │        200-What Is A Data Engineer 4.mp4
    │        200-What Is A Data Engineer 4.srt
    │        201-A Primer on ACID Transactions.txt
    │        201-OLTP vs OLAP.txt
    │        201-Types Of Databases.mp4
    │        201-Types Of Databases.srt
    │        202-Quick Note Upcoming Video.html
    │        203-Optional OLTP Databases.mp4
    │        203-Optional OLTP Databases.srt
    │        204-Optional Learn SQL.html
    │        205-Hadoop HDFS and MapReduce.mp4
    │        205-Hadoop HDFS and MapReduce.srt
    │        206-Apache Spark and Apache Flink.mp4
    │        206-Apache Spark and Apache Flink.srt
    │        207-Kafka and Stream Processing.mp4
    │        207-Kafka and Stream Processing.srt
    │       
    ├─14-Neural Networks Deep Learning Transfer Learning and TensorFlow 2
    │        208-Section Overview.mp4
    │        208-Section Overview.srt
    │        209-Deep Learning and Unstructured Data.mp4
    │        209-Deep Learning and Unstructured Data.srt
    │        210-Setting Up With Google.html
    │        211-Endtoend Dog Vision Notebook the project well be working through.txt
    │        211-Google Colab IO example how to get data in and out of your Colab notebook.txt
    │        211-Google Colab our workspace for the upcoming project.txt
    │        211-Introduction to Google Colab example notebook.txt
    │        211-Kaggle Dog Breed Identification Competition the basis of our upcoming project.txt
    │        211-Setting Up Google Colab.mp4
    │        211-Setting Up Google Colab.srt
    │        212-Google Colab FAQ things you should know about Google Colab.txt
    │        212-Google Colab our workspace for the upcoming project.txt
    │        212-Google Colab Workspace.mp4
    │        212-Google Colab Workspace.srt
    │        213-Google Colab IO example how to get data in and out of your Colab notebook.txt
    │        213-Kaggle Dog Breed Identification Competition Data.txt
    │        213-Uploading Project Data.mp4
    │        213-Uploading Project Data.srt
    │        214-Setting Up Our Data.mp4
    │        214-Setting Up Our Data.srt
    │        215-Setting Up Our Data 2.mp4
    │        215-Setting Up Our Data 2.srt
    │        216-Importing TensorFlow 2.mp4
    │        216-Importing TensorFlow 2.srt
    │        217-Loading TensorFlow 20 into a Colab Notebook if it isnt the default.txt
    │        217-Optional TensorFlow 20 Default Issue.mp4
    │        217-Optional TensorFlow 20 Default Issue.srt
    │        218-Google Colab example GPU usage.txt
    │        218-Using A GPU.mp4
    │        218-Using A GPU.srt
    │        219-Google Colab Example of GPU speed up versus CPU.txt
    │        219-Introduction to Google Colab example notebook.txt
    │        219-Optional GPU and Google Colab.mp4
    │        219-Optional GPU and Google Colab.srt
    │        220-Optional Reloading Colab Notebook.mp4
    │        220-Optional Reloading Colab Notebook.srt
    │        221-Documentation on how many images Google recommends for image problems】.txt
    │        221-Loading Our Data Labels.mp4
    │        221-Loading Our Data Labels.srt
    │        222-Preparing The Images.mp4
    │        222-Preparing The Images.srt
    │        223-Turning Data Labels Into Numbers.mp4
    │        223-Turning Data Labels Into Numbers.srt
    │        224-Blog post by Rachel Thomas of fastai on how and why you should create a validation set.txt
    │        224-Creating Our Own Validation Set.mp4
    │        224-Creating Our Own Validation Set.srt
    │        225-Documentation for loading images in TensorFlow.txt
    │        225-Preprocess Images.mp4
    │        225-Preprocess Images.srt
    │        225-TensorFlow guidelines for loading all kinds of data turning your data into Tensors.txt
    │        226-Preprocess Images 2.mp4
    │        226-Preprocess Images 2.srt
    │        227-Turning Data Into Batches.mp4
    │        227-Turning Data Into Batches.srt
    │        228-Turning Data Into Batches 2.mp4
    │        228-Turning Data Into Batches 2.srt
    │        228-Yann LeCuns OG of deep learning Tweet on Batch Sizes.txt
    │        229-Visualizing Our Data.mp4
    │        229-Visualizing Our Data.srt
    │        230-Preparing Our Inputs and Outputs.mp4
    │        230-Preparing Our Inputs and Outputs.srt
    │        230-TensorFlow Hub resource for pretrained deep learning models and more.txt
    │        231-Optional How machines learn and whats going on behind the scenes.html
    │        232-Andrei Karpathys talk on AI at Tesla.txt
    │        232-Building A Deep Learning Model.mp4
    │        232-Building A Deep Learning Model.srt
    │        232-MobileNetV2 the model were using on TensorFlow Hub.txt
    │        232-Papers with Code a great resource for .txt
    │        232-PyTorch Hub PyTorch version of TensorFlow Hub.txt
    │        232-TensorFlow Hub resource for pretrained deep learning models and more.txt
    │        233-Building A Deep Learning Model 2.mp4
    │        233-Building A Deep Learning Model 2.srt
    │        233-Keras in TensorFlow Overview Documentation.txt
    │        234-Building A Deep Learning Model 3.mp4
    │        234-Building A Deep Learning Model 3.srt
    │        234-MobileNetV2 the model were using architecture explanation by SikHo Tsang.txt
    │        234-Step by step breakdown of a convolutional neural network what MobileNetV2 is made of.txt
    │        234-The Softmax Function activation function we use in our model.txt
    │        235-Article How to choose loss & activation functions when building a deep learning model.txt
    │        235-Building A Deep Learning Model 4.mp4
    │        235-Building A Deep Learning Model 4.srt
    │        236-Summarizing Our Model.mp4
    │        236-Summarizing Our Model.srt
    │        237-Evaluating Our Model.mp4
    │        237-Evaluating Our Model.srt
    │        237-TensorBoard Callback Documentation.txt
    │        238-Early Stopping Callback a way to stop your model from training when it stops .txt
    │        238-Preventing Overfitting.mp4
    │        238-Preventing Overfitting.srt
    │        239-Training Your Deep Neural Network.mp4
    │        239-Training Your Deep Neural Network.srt
    │        240-Evaluating Performance With TensorBoard.mp4
    │        240-Evaluating Performance With TensorBoard.srt
    │        241-Make And Transform Predictions.mp4
    │        241-Make And Transform Predictions.srt
    │        242-TensorFlow documentation for the unbatch function.txt
    │        242-Transform Predictions To Text.mp4
    │        242-Transform Predictions To Text.srt
    │        243-Visualizing Model Predictions.mp4
    │        243-Visualizing Model Predictions.srt
    │        244-Visualizing And Evaluate Model Predictions 2.mp4
    │        244-Visualizing And Evaluate Model Predictions 2.srt
    │        245-Visualizing And Evaluate Model Predictions 3.mp4
    │        245-Visualizing And Evaluate Model Predictions 3.srt
    │        246-Saving And Loading A Trained Model.mp4
    │        246-Saving And Loading A Trained Model.srt
    │        247-Training Model On Full Dataset.mp4
    │        247-Training Model On Full Dataset.srt
    │        248-Dog Vision Prediction Probabilities Array.txt
    │        248-Making Predictions On Test Images.mp4
    │        248-Making Predictions On Test Images.srt
    │        249-Dog Vision Predictions with MobileNetV2 Ready for Kaggle Submission.txt
    │        249-Submitting Model to Kaggle.mp4
    │        249-Submitting Model to Kaggle.srt
    │        250-Endtoend Dog Vision Notebook from the videos.txt
    │        250-Endtoend Dog Vision Notebook with annotations.txt
    │        250-Making Predictions On Our Images.mp4
    │        250-Making Predictions On Our Images.srt
    │        251-Finishing Dog Vision Where to next.html
    │       
    ├─15-Storytelling Communication How To Present Your Work
    │        252-Section Overview.mp4
    │        252-Section Overview.srt
    │        253-Communicating Your Work.mp4
    │        253-Communicating Your Work.srt
    │        253-How to Think About Communicating and Sharing Your Work blog post.txt
    │        254-Communicating With Managers.mp4
    │        254-Communicating With Managers.srt
    │        255-Communicating With CoWorkers.mp4
    │        255-Communicating With CoWorkers.srt
    │        256-Weekend Project Principle.mp4
    │        256-Weekend Project Principle.srt
    │        257-Communicating With Outside World.mp4
    │        257-Communicating With Outside World.srt
    │        257-Devblog by Hashnode an easy and free way to create a blog you own.txt
    │        257-fasttemplate by fastai a template you can use for your blog on GitHub Pages.txt
    │        258-Storytelling.mp4
    │        258-Storytelling.srt
    │        259-Communicating and sharing your work Further reading.html
    │       
    ├─16-Career Advice Extra Bits
    │        260-Endorsements On LinkedIn.html
    │        261-Quick Note Upcoming Video.html
    │        262-What If I Dont Have Enough Experience.mp4
    │        262-What If I Dont Have Enough Experience.srt
    │        263-Learning Guideline.html
    │        264-Quick Note Upcoming Videos.html
    │        265-JTS Learn to Learn.mp4
    │        265-JTS Learn to Learn.srt
    │        266-JTS Start With Why.mp4
    │        266-JTS Start With Why.srt
    │        267-Quick Note Upcoming Videos.html
    │        268-CWD Git Github.mp4
    │        268-CWD Git Github.srt
    │        269-CWD Git Github 2.mp4
    │        269-CWD Git Github 2.srt
    │        270-Contributing To Open Source.mp4
    │        270-Contributing To Open Source.srt
    │        271-Contributing To Open Source 2.mp4
    │        271-Contributing To Open Source 2.srt
    │        272-Exercise Contribute To Open Source.html
    │        273-Coding Challenges.html
    │       
    ├─17-Learn Python
    │        274-What Is A Programming Language.mp4
    │        274-What Is A Programming Language.srt
    │        275-Python Interpreter.mp4
    │        275-Python Interpreter.srt
    │        275-pythonorg.txt
    │        276-Glotio.txt
    │        276-How To Run Python Code.mp4
    │        276-How To Run Python Code.srt
    │        276-Replit.txt
    │        277-Our First Python Program.mp4
    │        277-Our First Python Program.srt
    │        278-Latest Version Of Python.mp4
    │        278-Latest Version Of Python.srt
    │        279-Python 2 vs Python 3 another one.txt
    │        279-Python 2 vs Python 3.mp4
    │        279-Python 2 vs Python 3.srt
    │        279-Python 2 vs Python 3.txt
    │        279-The Story of Python.txt
    │        280-Exercise How Does Python Work.mp4
    │        280-Exercise How Does Python Work.srt
    │        281-Learning Python.mp4
    │        281-Learning Python.srt
    │        282-Python Data Types.mp4
    │        282-Python Data Types.srt
    │        283-How To Succeed.html
    │        284-Floating point numbers.txt
    │        284-Numbers.mp4
    │        284-Numbers.srt
    │        285-Math Functions.mp4
    │        285-Math Functions.srt
    │        286-DEVELOPER FUNDAMENTALS I.mp4
    │        287-Exercise Repl.txt
    │        287-Operator Precedence.mp4
    │        287-Operator Precedence.srt
    │        288-Exercise Operator Precedence.html
    │        288-Exercise Repl.txt
    │        289-Base Numbers.txt
    │        289-Optional bin and complex.mp4
    │        289-Optional bin and complex.srt
    │        290-Python Keywords.txt
    │        290-Variables.mp4
    │        290-Variables.srt
    │        291-Expressions vs Statements.mp4
    │        291-Expressions vs Statements.srt
    │        292-Augmented Assignment Operator.mp4
    │        292-Augmented Assignment Operator.srt
    │        292-Exercise Repl.txt
    │        293-Strings.mp4
    │        293-Strings.srt
    │        294-String Concatenation.mp4
    │        294-String Concatenation.srt
    │        295-Type Conversion.mp4
    │        295-Type Conversion.srt
    │        296-Escape Sequences.mp4
    │        296-Escape Sequences.srt
    │        297-Exercise Repl.txt
    │        297-Formatted Strings.mp4
    │        297-Formatted Strings.srt
    │        298-Exercise Repl.txt
    │        298-String Indexes.mp4
    │        298-String Indexes.srt
    │        299-Immutability.mp4
    │        299-Immutability.srt
    │        300-Built in Functions.txt
    │        300-BuiltIn Functions Methods.mp4
    │        300-BuiltIn Functions Methods.srt
    │        300-String Methods.txt
    │        301-Booleans.mp4
    │        301-Booleans.srt
    │        302-Exercise Type Conversion.mp4
    │        302-Exercise Type Conversion.srt
    │        303-DEVELOPER FUNDAMENTALS II.mp4
    │        303-DEVELOPER FUNDAMENTALS II.srt
    │        303-Python Comments Best Practices.txt
    │        304-Exercise Password Checker.mp4
    │        304-Exercise Password Checker.srt
    │        305-Lists.mp4
    │        305-Lists.srt
    │        306-Exercise Repl.txt
    │        306-List Slicing.mp4
    │        306-List Slicing.srt
    │        307-Exercise Repl.txt
    │        307-Matrix.mp4
    │        307-Matrix.srt
    │        308-List Methods.mp4
    │        308-List Methods.srt
    │        308-List Methods.txt
    │        309-Exercise Repl.txt
    │        309-List Methods 2.mp4
    │        309-List Methods 2.srt
    │        309-Python Keywords.txt
    │        310-List Methods 3.mp4
    │        310-List Methods 3.srt
    │        311-Common List Patterns.mp4
    │        311-Common List Patterns.srt
    │        311-Exercise Repl.txt
    │        312-List Unpacking.mp4
    │        312-List Unpacking.srt
    │        313-None.mp4
    │        313-None.srt
    │        314-Dictionaries.mp4
    │        314-Dictionaries.srt
    │        315-DEVELOPER FUNDAMENTALS III.mp4
    │        315-DEVELOPER FUNDAMENTALS III.srt
    │        316-Dictionary Keys.mp4
    │        316-Dictionary Keys.srt
    │        317-Dictionary Methods.mp4
    │        317-Dictionary Methods.srt
    │        317-Dictionary Methods.txt
    │        318-Dictionary Methods 2.mp4
    │        318-Dictionary Methods 2.srt
    │        318-Exercise Repl.txt
    │        319-Tuples.mp4
    │        319-Tuples.srt
    │        320-Tuple Methods.txt
    │        320-Tuples 2.mp4
    │        320-Tuples 2.srt
    │        321-Sets.mp4
    │        321-Sets.srt
    │        322-Exercise Repl.txt
    │        322-Sets 2.mp4
    │        322-Sets 2.srt
    │        322-Sets Methods.txt
    │       
    ├─18-Learn Python Part 2
    │        323-Breaking The Flow.mp4
    │        323-Breaking The Flow.srt
    │        324-Conditional Logic.mp4
    │        324-Conditional Logic.srt
    │        325-Indentation In Python.mp4
    │        325-Indentation In Python.srt
    │        326-Truthy vs Falsey Stackoverflow.txt
    │        326-Truthy vs Falsey.mp4
    │        326-Truthy vs Falsey.srt
    │        327-Ternary Operator.mp4
    │        327-Ternary Operator.srt
    │        328-Short Circuiting.mp4
    │        328-Short Circuiting.srt
    │        329-Logical Operators.mp4
    │        329-Logical Operators.srt
    │        330-Exercise Logical Operators.mp4
    │        330-Exercise Logical Operators.srt
    │        331-is vs.mp4
    │        331-is vs.srt
    │        332-For Loops.mp4
    │        332-For Loops.srt
    │        333-Iterables.mp4
    │        333-Iterables.srt
    │        334-Exercise Tricky Counter.mp4
    │        334-Exercise Tricky Counter.srt
    │        334-Solution Repl.txt
    │        335-range.mp4
    │        335-range.srt
    │        336-enumerate.mp4
    │        336-enumerate.srt
    │        337-While Loops.mp4
    │        337-While Loops.srt
    │        338-While Loops 2.mp4
    │        338-While Loops 2.srt
    │        339-break continue pass.mp4
    │        339-break continue pass.srt
    │        340-Exercise Repl.txt
    │        340-Our First GUI.mp4
    │        340-Our First GUI.srt
    │        340-Solution Repl.txt
    │        341-DEVELOPER FUNDAMENTALS IV.mp4
    │        341-DEVELOPER FUNDAMENTALS IV.srt
    │        342-Exercise Find Duplicates.mp4
    │        342-Exercise Find Duplicates.srt
    │        342-Solution Repl.txt
    │        343-Functions.mp4
    │        343-Functions.srt
    │        344-Parameters and Arguments.mp4
    │        344-Parameters and Arguments.srt
    │        345-Default Parameters and Keyword Arguments.mp4
    │        345-Default Parameters and Keyword Arguments.srt
    │        346-return.mp4
    │        346-return.srt
    │        347-Exercise Tesla.html
    │        348-Methods vs Functions.mp4
    │        348-Methods vs Functions.srt
    │        349-Docstrings.mp4
    │        349-Docstrings.srt
    │        350-Clean Code.mp4
    │        350-Clean Code.srt
    │        351-args and kwargs.mp4
    │        351-args and kwargs.srt
    │        352-Exercise Functions.mp4
    │        352-Exercise Functions.srt
    │        352-Solution Repl.txt
    │        353-Scope.mp4
    │        353-Scope.srt
    │        354-Scope Rules.mp4
    │        354-Scope Rules.srt
    │        355-global Keyword.mp4
    │        355-global Keyword.srt
    │        356-nonlocal Keyword.mp4
    │        356-nonlocal Keyword.srt
    │        356-Solution Repl.txt
    │        357-Why Do We Need Scope.mp4
    │        358-Pure Functions.mp4
    │        358-Pure Functions.srt
    │        359-map.mp4
    │        359-map.srt
    │        360-filter.mp4
    │        360-filter.srt
    │        361-zip.mp4
    │        361-zip.srt
    │        362-reduce.mp4
    │        362-reduce.srt
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    │        363-List Comprehensions.srt
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