
网盘:百度 | 学分:5,VIP免费 | 发布:2024-05-19 | 查看:0 | 更新:2024-05-19 | 大数据/人工智能
udemy-机器学习和数据科学训练营2023年
网盘:百度 | 学分:5,VIP免费 | 发布:2024-05-19 | 查看:0 | 更新:2024-05-19 | 大数据/人工智能
udemy-机器学习和数据科学训练营2023年
├─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 &AMp; 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
│ 363-List ComPrehensions.mp4
│ 363-List ComPrehensions.srt
│ 364-Set ComPrehensions.mp4
│ 364-Set ComPrehensions.srt
│ 365-Exercise ComPrehensions.mp4
│ 365-Exercise ComPrehensions.srt
│ 365-Exercise Repl.txt
│ 365-Solution Repl.txt
│ 366-python ExAM Testing Your Understanding.html
│ 367-Modules in python.mp4
│ 367-Modules in python.srt
│ 368-Quick Note Upcoming Videos.html
│ 369-Optional PyCharm.mp4
│ 369-Optional PyCharm.srt
│ 370-Packages in python.mp4
│ 370-Packages in python.srt
│ 371-Different Ways To IMport.mp4
│ 371-Different Ways To IMport.srt
│ 372-NEXT StePS.html
│ 373-Bonus Resource python Cheatsheet.html
│
├─19-Extra Learn ADvanced Statistics and Mathematics for FREE
│ 374-Statistics and Mathematics.html
│
├─20-Where To Go From Here
│ 375-Become An Alumni.html
│ 376-Thank You.mp4
│ 376-Thank You.srt
│ 377-Thank You Part 2.html
│
└─21-BONUS SECTION
378-Special Bonus Lecture.html
*声明:课程资源购自网络,版权归原作者所有,仅供参考学习使用,严禁外传及商用,若侵犯到您的权益请联系客服删除。