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| 001 Course Outline.en_US.srt |
8.53Кб |
| 001 Course Outline.mp4 |
144.64Мб |
| 002 Join Our Online Classroom!.html |
2.78Кб |
| 003 Exercise_ Meet The Community.html |
2.98Кб |
| 004 Your First Day.en_US.srt |
5.05Кб |
| 004 Your First Day.mp4 |
43.05Мб |
| 005 What Is Machine Learning_.en_US.srt |
8.33Кб |
| 005 What Is Machine Learning_.mp4 |
29.96Мб |
| 006 AI_Machine Learning_Data Science.en_US.srt |
6.13Кб |
| 006 AI_Machine Learning_Data Science.mp4 |
22.75Мб |
| 007 Exercise_ Machine Learning Playground.en_US.srt |
7.76Кб |
| 007 Exercise_ Machine Learning Playground.mp4 |
65.73Мб |
| 007 Teachable-Machine.txt |
41б |
| 008 How Did We Get Here_.en_US.srt |
6.83Кб |
| 008 How Did We Get Here_.mp4 |
39.17Мб |
| 009 Exercise_ YouTube Recommendation Engine.en_US.srt |
5.41Кб |
| 009 Exercise_ YouTube Recommendation Engine.mp4 |
13.12Мб |
| 009 Machine-Learning-Playground.txt |
28б |
| 010 Types of Machine Learning.en_US.srt |
5.09Кб |
| 010 Types of Machine Learning.mp4 |
15.04Мб |
| 011 Are You Getting It Yet_.html |
645б |
| 012 What Is Machine Learning_ Round 2.en_US.srt |
5.86Кб |
| 012 What Is Machine Learning_ Round 2.mp4 |
19.15Мб |
| 013 Section Review.en_US.srt |
2.25Кб |
| 013 Section Review.mp4 |
4.06Мб |
| 014 Section Overview.en_US.srt |
4.48Кб |
| 014 Section Overview.mp4 |
9.63Мб |
| 015 Introducing Our Framework.en_US.srt |
3.57Кб |
| 015 Introducing Our Framework.mp4 |
6.36Мб |
| 016 6 Step Machine Learning Framework.en_US.srt |
6.40Кб |
| 016 6 Step Machine Learning Framework.mp4 |
15.22Мб |
| 016 A-6-Step-Field-Guide-for-Machine-Learning-Modelling-blog-post-.txt |
87б |
| 017 Types of Machine Learning Problems.en_US.srt |
13.51Кб |
| 017 Types of Machine Learning Problems.mp4 |
33.12Мб |
| 018 Types of Data.en_US.srt |
6.29Кб |
| 018 Types of Data.mp4 |
33.50Мб |
| 019 Types of Evaluation.en_US.srt |
4.19Кб |
| 019 Types of Evaluation.mp4 |
9.79Мб |
| 020 Features In Data.en_US.srt |
6.51Кб |
| 020 Features In Data.mp4 |
24.47Мб |
| 021 Modelling - Splitting Data.en_US.srt |
7.43Кб |
| 021 Modelling - Splitting Data.mp4 |
16.75Мб |
| 022 Modelling - Picking the Model.en_US.srt |
5.98Кб |
| 022 Modelling - Picking the Model.mp4 |
13.10Мб |
| 023 Modelling - Tuning.en_US.srt |
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| 023 Modelling - Tuning.mp4 |
9.28Мб |
| 024 Modelling - Comparison.en_US.srt |
12.61Кб |
| 024 Modelling - Comparison.mp4 |
27.28Мб |
| 025 Overfitting and Underfitting Definitions.html |
2.21Кб |
| 026 Experimentation.en_US.srt |
4.78Кб |
| 026 Experimentation.mp4 |
18.89Мб |
| 027 Tools We Will Use.en_US.srt |
5.77Кб |
| 027 Tools We Will Use.mp4 |
20.53Мб |
| 028 Optional_ Elements of AI.html |
1.43Кб |
| 029 The 2 Paths.en_US.srt |
4.52Кб |
| 029 The 2 Paths.mp4 |
6.99Мб |
| 030 Python + Machine Learning Monthly.html |
1.19Кб |
| 031 Section Overview.en_US.srt |
2.02Кб |
| 031 Section Overview.mp4 |
3.93Мб |
| 032 Introducing Our Tools.en_US.srt |
4.18Кб |
| 032 Introducing Our Tools.mp4 |
16.38Мб |
| 033 conda-cheatsheet.pdf |
201.29Кб |
| 033 Conda-documentation.txt |
33б |
| 033 Getting-started-with-Conda-documentation-.txt |
79б |
| 033 Getting-your-computer-ready-for-machine-learning-How-what-and-why-you-should-use-Anaconda-Miniconda-and-Conda-blog-post-.txt |
107б |
| 033 What is Conda_.en_US.srt |
3.29Кб |
| 033 What is Conda_.mp4 |
7.38Мб |
| 034 Conda Environments.en_US.srt |
5.92Кб |
| 034 Conda Environments.mp4 |
24.72Мб |
| 035 Mac Environment Setup.en_US.srt |
23.06Кб |
| 035 Mac Environment Setup.mp4 |
262.60Мб |
| 035 Miniconda-download-documentation.txt |
47б |
| 036 Mac Environment Setup 2.en_US.srt |
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| 036 Mac Environment Setup 2.mp4 |
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| 037 Miniconda-download-documentation.txt |
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| 037 Windows Environment Setup.en_US.srt |
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| 037 Windows Environment Setup.mp4 |
59.40Мб |
| 038 Windows Environment Setup 2.en_US.srt |
30.38Кб |
| 038 Windows Environment Setup 2.mp4 |
349.11Мб |
| 039 Linux Environment Setup.html |
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| 040 Conda-documentation-on-sharing-an-environment.txt |
112б |
| 040 Sharing your Conda Environment.html |
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| 041 6-step-ml-framework.png |
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| 041 Dataquest-Jupyter-Notebook-for-Beginners-Tutorial.txt |
57б |
| 041 heart-disease.csv |
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| 041 Jupyter-Notebook-documentation.txt |
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| 041 Jupyter Notebook Walkthrough.en_US.srt |
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| 041 Jupyter Notebook Walkthrough.mp4 |
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| 042 Jupyter Notebook Walkthrough 2.en_US.srt |
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| 042 Jupyter Notebook Walkthrough 2.mp4 |
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| 043 Jupyter Notebook Walkthrough 3.en_US.srt |
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| 043 Jupyter Notebook Walkthrough 3.mp4 |
127.78Мб |
| 044 Section Overview.en_US.srt |
3.59Кб |
| 044 Section Overview.mp4 |
7.83Мб |
| 045 Downloading Workbooks and Assignments.html |
1.42Кб |
| 046 10-minutes-to-pandas-from-the-pandas-documentation-.txt |
72б |
| 046 Introduction-to-Pandas-Jupyter-Notebook-from-the-upcoming-videos-.txt |
131б |
| 046 Introduction-to-Pandas-Jupyter-Notebook-with-annotations-.txt |
125б |
| 046 Pandas-Documentation.txt |
46б |
| 046 Pandas Introduction.en_US.srt |
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| 046 Pandas Introduction.mp4 |
17.93Мб |
| 047 pandas-anatomy-of-a-dataframe.png |
333.24Кб |
| 047 Series, Data Frames and CSVs.en_US.srt |
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| 047 Series, Data Frames and CSVs.mp4 |
166.07Мб |
| 048 Data from URLs.html |
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| 049 Describing Data with Pandas.en_US.srt |
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| 049 Describing Data with Pandas.mp4 |
112.57Мб |
| 050 car-sales.csv |
369б |
| 050 Selecting and Viewing Data with Pandas.en_US.srt |
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| 050 Selecting and Viewing Data with Pandas.mp4 |
106.88Мб |
| 051 Selecting and Viewing Data with Pandas Part 2.en_US.srt |
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| 051 Selecting and Viewing Data with Pandas Part 2.mp4 |
187.25Мб |
| 052 car-sales-missing-data.csv |
287б |
| 052 Jake-VanderPlass-Data-Manipulation-with-Pandas.txt |
86б |
| 052 Manipulating Data.en_US.srt |
17.33Кб |
| 052 Manipulating Data.mp4 |
181.28Мб |
| 053 Manipulating Data 2.en_US.srt |
13.27Кб |
| 053 Manipulating Data 2.mp4 |
156.04Мб |
| 053 pandas-anatomy-of-a-dataframe.png |
333.24Кб |
| 054 Introduction-to-Pandas-Jupyter-Notebook-from-the-videos-.txt |
131б |
| 054 Introduction-to-Pandas-Jupyter-Notebook-with-annotations-.txt |
125б |
| 054 Manipulating Data 3.en_US.srt |
13.15Кб |
| 054 Manipulating Data 3.mp4 |
137.81Мб |
| 055 Assignment_ Pandas Practice.html |
2.52Кб |
| 056 Course-notebooks-Github.txt |
48б |
| 056 Google-Colab.txt |
35б |
| 056 How To Download The Course Assignments.en_US.srt |
10.62Кб |
| 056 How To Download The Course Assignments.mp4 |
45.44Мб |
| 057 Section Overview.en_US.srt |
3.00Кб |
| 057 Section Overview.mp4 |
22.55Мб |
| 058 Introduction-to-NumPy-Jupyter-Notebook-from-the-upcoming-videos-.txt |
130б |
| 058 Introduction-to-NumPy-Jupyter-Notebook-with-annotations-.txt |
124б |
| 058 NumPy-Documentation.txt |
23б |
| 058 NumPy Introduction.en_US.srt |
7.22Кб |
| 058 NumPy Introduction.mp4 |
21.62Мб |
| 059 Quick Note_ Correction In Next Video.html |
1.74Кб |
| 060 NumPy DataTypes and Attributes.en_US.srt |
18.43Кб |
| 060 NumPy DataTypes and Attributes.mp4 |
94.05Мб |
| 061 Creating NumPy Arrays.en_US.srt |
11.86Кб |
| 061 Creating NumPy Arrays.mp4 |
77.89Мб |
| 062 NumPy Random Seed.en_US.srt |
9.31Кб |
| 062 NumPy Random Seed.mp4 |
61.99Мб |
| 063 Viewing Arrays and Matrices.en_US.srt |
12.33Кб |
| 063 Viewing Arrays and Matrices.mp4 |
104.01Мб |
| 064 Manipulating Arrays.en_US.srt |
15.49Кб |
| 064 Manipulating Arrays.mp4 |
119.44Мб |
| 064 Standard-deviation-and-variance-explained.txt |
56б |
| 065 Manipulating Arrays 2.en_US.srt |
11.03Кб |
| 065 Manipulating Arrays 2.mp4 |
101.87Мб |
| 065 Standard-deviation-and-variance-explained.txt |
56б |
| 066 Standard Deviation and Variance.en_US.srt |
8.95Кб |
| 066 Standard Deviation and Variance.mp4 |
61.83Мб |
| 066 Standard-deviation-and-variance-explained.txt |
56б |
| 067 Reshape and Transpose.en_US.srt |
9.11Кб |
| 067 Reshape and Transpose.mp4 |
91.58Мб |
| 068 Dot Product vs Element Wise.en_US.srt |
14.68Кб |
| 068 Dot Product vs Element Wise.mp4 |
122.83Мб |
| 068 Matrix-Multiplication-Explained.txt |
59б |
| 069 Exercise_ Nut Butter Store Sales.en_US.srt |
16.21Кб |
| 069 Exercise_ Nut Butter Store Sales.mp4 |
135.03Мб |
| 070 Comparison Operators.en_US.srt |
5.00Кб |
| 070 Comparison Operators.mp4 |
38.52Мб |
| 071 Sorting Arrays.en_US.srt |
8.40Кб |
| 071 Sorting Arrays.mp4 |
39.31Мб |
| 072 Introduction-to-NumPy-Jupyter-Notebook-from-the-videos-.txt |
130б |
| 072 Introduction-to-NumPy-Jupyter-Notebook-with-annotations-.txt |
124б |
| 072 numpy-images.zip |
7.27Мб |
| 072 Turn Images Into NumPy Arrays.en_US.srt |
9.98Кб |
| 072 Turn Images Into NumPy Arrays.mp4 |
165.01Мб |
| 073 Assignment_ NumPy Practice.html |
2.64Кб |
| 074 Optional_ Extra NumPy resources.html |
1.50Кб |
| 075 Section Overview.en_US.srt |
2.57Кб |
| 075 Section Overview.mp4 |
6.09Мб |
| 076 Introduction-to-Matplotlib-Jupyter-Notebook-from-the-upcoming-videos-.txt |
135б |
| 076 Matplotlib-Documentation.txt |
43б |
| 076 Matplotlib Introduction.en_US.srt |
7.72Кб |
| 076 Matplotlib Introduction.mp4 |
35.02Мб |
| 077 Importing And Using Matplotlib.en_US.srt |
15.38Кб |
| 077 Importing And Using Matplotlib.mp4 |
147.20Мб |
| 078 Anatomy Of A Matplotlib Figure.en_US.srt |
13.53Кб |
| 078 Anatomy Of A Matplotlib Figure.mp4 |
91.76Мб |
| 078 matplotlib-anatomy-of-a-plot.png |
369.39Кб |
| 078 matplotlib-anatomy-of-a-plot-with-code.png |
654.77Кб |
| 079 Scatter Plot And Bar Plot.en_US.srt |
14.02Кб |
| 079 Scatter Plot And Bar Plot.mp4 |
75.53Мб |
| 080 Histograms And Subplots.en_US.srt |
11.88Кб |
| 080 Histograms And Subplots.mp4 |
98.43Мб |
| 081 Subplots Option 2.en_US.srt |
6.12Кб |
| 081 Subplots Option 2.mp4 |
54.63Мб |
| 082 Quick Tip_ Data Visualizations.en_US.srt |
2.25Кб |
| 082 Quick Tip_ Data Visualizations.mp4 |
6.80Мб |
| 083 Plotting From Pandas DataFrames.en_US.srt |
8.63Кб |
| 083 Plotting From Pandas DataFrames.mp4 |
90.10Мб |
| 084 Quick Note_ Regular Expressions.html |
1.09Кб |
| 085 Plotting From Pandas DataFrames 2.en_US.srt |
13.05Кб |
| 085 Plotting From Pandas DataFrames 2.mp4 |
177.54Мб |
| 086 Plotting from Pandas DataFrames 3.en_US.srt |
11.00Кб |
| 086 Plotting from Pandas DataFrames 3.mp4 |
127.49Мб |
| 087 heart-disease.csv |
11.06Кб |
| 087 Plotting from Pandas DataFrames 4.en_US.srt |
9.03Кб |
| 087 Plotting from Pandas DataFrames 4.mp4 |
53.53Мб |
| 088 Plotting from Pandas DataFrames 5.en_US.srt |
11.15Кб |
| 088 Plotting from Pandas DataFrames 5.mp4 |
93.42Мб |
| 089 Plotting from Pandas DataFrames 6.en_US.srt |
10.63Кб |
| 089 Plotting from Pandas DataFrames 6.mp4 |
121.51Мб |
| 090 Plotting from Pandas DataFrames 7.en_US.srt |
14.33Кб |
| 090 Plotting from Pandas DataFrames 7.mp4 |
220.71Мб |
| 091 Customizing Your Plots.en_US.srt |
13.36Кб |
| 091 Customizing Your Plots.mp4 |
133.27Мб |
| 092 Customizing Your Plots 2.en_US.srt |
12.71Кб |
| 092 Customizing Your Plots 2.mp4 |
235.99Мб |
| 093 Introduction-to-Matplotlib-Notebook-from-the-videos-.txt |
135б |
| 093 Saving And Sharing Your Plots.en_US.srt |
5.61Кб |
| 093 Saving And Sharing Your Plots.mp4 |
92.85Мб |
| 094 Assignment_ Matplotlib Practice.html |
2.53Кб |
| 095 Section Overview.en_US.srt |
3.92Кб |
| 095 Section Overview.mp4 |
8.73Мб |
| 096 Introduction-to-Scikit-Learn-Jupyter-Notebook-from-the-upcoming-videos-.txt |
137б |
| 096 Introduction-to-Scikit-Learn-Jupyter-Notebook-with-annotations-.txt |
131б |
| 096 Scikit-Learn-Documentation.txt |
48б |
| 096 Scikit-learn Introduction.en_US.srt |
10.19Кб |
| 096 Scikit-learn Introduction.mp4 |
26.89Мб |
| 097 Quick Note_ Upcoming Video.html |
875б |
| 098 Refresher_ What Is Machine Learning_.en_US.srt |
6.09Кб |
| 098 Refresher_ What Is Machine Learning_.mp4 |
33.65Мб |
| 099 Quick Note_ Upcoming Videos.html |
1.47Кб |
| 100 Scikit-learn Cheatsheet.en_US.srt |
9.72Кб |
| 100 Scikit-learn Cheatsheet.mp4 |
139.93Мб |
| 100 Scikit-Learn-Reference-Notebook.txt |
134б |
| 101 Example-Scikit-Learn-Workflow-Notebook.txt |
132б |
| 101 Typical scikit-learn Workflow.en_US.srt |
30.40Кб |
| 101 Typical scikit-learn Workflow.mp4 |
337.47Мб |
| 102 Optional_ Debugging Warnings In Jupyter.en_US.srt |
24.57Кб |
| 102 Optional_ Debugging Warnings In Jupyter.mp4 |
323.08Мб |
| 103 Getting Your Data Ready_ Splitting Your Data.en_US.srt |
11.57Кб |
| 103 Getting Your Data Ready_ Splitting Your Data.mp4 |
109.40Мб |
| 103 scikit-learn-data.zip |
20.83Кб |
| 104 Quick Tip_ Clean, Transform, Reduce.en_US.srt |
6.17Кб |
| 104 Quick Tip_ Clean, Transform, Reduce.mp4 |
15.45Мб |
| 105 Getting Your Data Ready_ Convert Data To Numbers.en_US.srt |
21.77Кб |
| 105 Getting Your Data Ready_ Convert Data To Numbers.mp4 |
238.13Мб |
| 106 Getting Your Data Ready_ Handling Missing Values With Pandas.en_US.srt |
16.27Кб |
| 106 Getting Your Data Ready_ Handling Missing Values With Pandas.mp4 |
187.61Мб |
| 107 Extension_ Feature Scaling.html |
3.41Кб |
| 108 Note_ Correction in the upcoming video (splitting data).html |
2.63Кб |
| 109 Getting Your Data Ready_ Handling Missing Values With Scikit-learn.en_US.srt |
22.24Кб |
| 109 Getting Your Data Ready_ Handling Missing Values With Scikit-learn.mp4 |
242.58Мб |
| 110 Choosing The Right Model For Your Data.en_US.srt |
20.47Кб |
| 110 Choosing The Right Model For Your Data.mp4 |
262.61Мб |
| 110 Scikit-Learn-machine-learning-map-how-to-choose-the-right-machine-learning-model-.txt |
73б |
| 111 Choosing The Right Model For Your Data 2 (Regression).en_US.srt |
11.49Кб |
| 111 Choosing The Right Model For Your Data 2 (Regression).mp4 |
161.05Мб |
| 112 Quick Note_ Decision Trees.html |
706б |
| 113 Quick Tip_ How ML Algorithms Work.en_US.srt |
1.83Кб |
| 113 Quick Tip_ How ML Algorithms Work.mp4 |
7.28Мб |
| 114 Choosing The Right Model For Your Data 3 (Classification).en_US.srt |
16.43Кб |
| 114 Choosing The Right Model For Your Data 3 (Classification).mp4 |
217.07Мб |
| 115 Fitting A Model To The Data.en_US.srt |
8.97Кб |
| 115 Fitting A Model To The Data.mp4 |
67.57Мб |
| 116 Making Predictions With Our Model.en_US.srt |
11.58Кб |
| 116 Making Predictions With Our Model.mp4 |
118.58Мб |
| 117 predict() vs predict_proba().en_US.srt |
11.09Кб |
| 117 predict() vs predict_proba().mp4 |
67.01Мб |
| 118 Making Predictions With Our Model (Regression).en_US.srt |
8.75Кб |
| 118 Making Predictions With Our Model (Regression).mp4 |
76.48Мб |
| 119 Evaluating A Machine Learning Model (Score).en_US.srt |
12.34Кб |
| 119 Evaluating A Machine Learning Model (Score).mp4 |
160.14Мб |
| 120 Evaluating A Machine Learning Model 2 (Cross Validation).en_US.srt |
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| 120 Evaluating A Machine Learning Model 2 (Cross Validation).mp4 |
166.17Мб |
| 121 Evaluating A Classification Model 1 (Accuracy).en_US.srt |
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| 121 Evaluating A Classification Model 1 (Accuracy).mp4 |
52.94Мб |
| 122 Evaluating A Classification Model 2 (ROC Curve).en_US.srt |
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| 122 Evaluating A Classification Model 2 (ROC Curve).mp4 |
99.08Мб |
| 123 Evaluating A Classification Model 3 (ROC Curve).en_US.srt |
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| 123 Evaluating A Classification Model 3 (ROC Curve).mp4 |
85.74Мб |
| 124 Reading Extension_ ROC Curve + AUC.html |
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| 125 Evaluating A Classification Model 4 (Confusion Matrix).en_US.srt |
14.47Кб |
| 125 Evaluating A Classification Model 4 (Confusion Matrix).mp4 |
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| 126 Evaluating A Classification Model 5 (Confusion Matrix).en_US.srt |
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| 126 Evaluating A Classification Model 5 (Confusion Matrix).mp4 |
96.09Мб |
| 127 Evaluating A Classification Model 6 (Classification Report).en_US.srt |
13.98Кб |
| 127 Evaluating A Classification Model 6 (Classification Report).mp4 |
152.06Мб |
| 128 Evaluating A Regression Model 1 (R2 Score).en_US.srt |
11.50Кб |
| 128 Evaluating A Regression Model 1 (R2 Score).mp4 |
123.65Мб |
| 129 Evaluating A Regression Model 2 (MAE).en_US.srt |
5.46Кб |
| 129 Evaluating A Regression Model 2 (MAE).mp4 |
50.04Мб |
| 130 Evaluating A Regression Model 3 (MSE).en_US.srt |
8.87Кб |
| 130 Evaluating A Regression Model 3 (MSE).mp4 |
79.39Мб |
| 131 Machine Learning Model Evaluation.html |
7.59Кб |
| 132 Evaluating A Model With Cross Validation and Scoring Parameter.en_US.srt |
17.25Кб |
| 132 Evaluating A Model With Cross Validation and Scoring Parameter.mp4 |
157.80Мб |
| 133 Evaluating A Model With Scikit-learn Functions.en_US.srt |
15.68Кб |
| 133 Evaluating A Model With Scikit-learn Functions.mp4 |
169.44Мб |
| 134 Improving A Machine Learning Model.en_US.srt |
14.31Кб |
| 134 Improving A Machine Learning Model.mp4 |
161.77Мб |
| 135 Tuning Hyperparameters.en_US.srt |
29.45Кб |
| 135 Tuning Hyperparameters.mp4 |
311.45Мб |
| 136 Tuning Hyperparameters 2.en_US.srt |
16.30Кб |
| 136 Tuning Hyperparameters 2.mp4 |
203.74Мб |
| 137 Tuning Hyperparameters 3.en_US.srt |
18.14Кб |
| 137 Tuning Hyperparameters 3.mp4 |
212.64Мб |
| 138 Note_ Metric Comparison Improvement.html |
2.66Кб |
| 139 Quick Tip_ Correlation Analysis.en_US.srt |
2.97Кб |
| 139 Quick Tip_ Correlation Analysis.mp4 |
31.12Мб |
| 140 Saving And Loading A Model.en_US.srt |
9.47Кб |
| 140 Saving And Loading A Model.mp4 |
78.70Мб |
| 141 Saving And Loading A Model 2.en_US.srt |
8.62Кб |
| 141 Saving And Loading A Model 2.mp4 |
86.30Мб |
| 142 Putting It All Together.en_US.srt |
28.22Кб |
| 142 Putting It All Together.mp4 |
284.69Мб |
| 142 Read-Corrected-splitting-data-notebook.txt |
74б |
| 143 Introduction-to-Scikit-Learn-Jupyter-Notebook-from-the-videos-.txt |
137б |
| 143 Introduction-to-Scikit-Learn-Jupyter-Notebook-with-annotations-.txt |
131б |
| 143 Putting It All Together 2.en_US.srt |
15.48Кб |
| 143 Putting It All Together 2.mp4 |
212.77Мб |
| 144 Scikit-Learn Practice.html |
2.54Кб |
| 145 Milestone Projects!.html |
1.19Кб |
| 146 Section Overview.en_US.srt |
2.98Кб |
| 146 Section Overview.mp4 |
7.08Мб |
| 147 End-to-end-Heart-Disease-Classification-Notebook-same-as-in-videos-.txt |
147б |
| 147 End-to-end-Heart-Disease-Classification-Notebook-with-annotations-.txt |
141б |
| 147 Project Overview.en_US.srt |
9.65Кб |
| 147 Project Overview.mp4 |
22.22Мб |
| 147 Structured-Data-Projects-on-GitHub.txt |
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| 150 Getting Our Tools Ready.en_US.srt |
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| 151 Exploring Our Data.en_US.srt |
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| 152 Finding Patterns.en_US.srt |
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| 154 Finding Patterns 3.mp4 |
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| 155 Preparing Our Data For Machine Learning.en_US.srt |
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| 155 Preparing Our Data For Machine Learning.mp4 |
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| 156 Choosing The Right Models.en_US.srt |
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| 165 Finding The Most Important Features.en_US.srt |
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| 166 End-to-end-Heart-Disease-Classification-Notebook-same-as-in-videos-.txt |
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| 166 End-to-end-Heart-Disease-Classification-Notebook-with-annotations-.txt |
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| 168 End-to-end-Bluebook-Bulldozer-Regression-Notebook-same-as-in-videos-.txt |
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| 168 End-to-end-Bluebook-Bulldozer-Regression-Notebook-with-annotations-.txt |
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| 168 Kaggle-Bluebook-for-Bulldozers-Competition.txt |
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| 168 Structured-Data-Projects-on-GitHub.txt |
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| 170 Step 1~4 Framework Setup.en_US.srt |
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| 171 Downloading the data for the next two projects.html |
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| 172 Exploring Our Data.en_US.srt |
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| 176 Pandas-Categorical-Datatype-Documentation.txt |
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| 178 Fitting A Machine Learning Model.en_US.srt |
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| 182 Reducing Data.en_US.srt |
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| 183 RandomizedSearchCV.en_US.srt |
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| 184 Improving Hyperparameters.en_US.srt |
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| 186 Making Predictions.en_US.srt |
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| 187 End-to-end-Bluebook-Bulldozer-Regression-Notebook-same-as-in-videos-.txt |
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| 187 End-to-end-Bluebook-Bulldozer-Regression-Notebook-with-annotations-.txt |
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| 187 Feature Importance.en_US.srt |
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| 188 Data Engineering Introduction.en_US.srt |
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| 189 Kaggle.txt |
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| 189 What Is Data_.en_US.srt |
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| 194 A-Primer-on-ACID-Transactions.txt |
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| 194 OLTP-vs-OLAP.txt |
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| 194 Types Of Databases.en_US.srt |
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| 197 Optional_ Learn SQL.html |
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| 198 Hadoop, HDFS and MapReduce.en_US.srt |
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| 198 Hadoop, HDFS and MapReduce.mp4 |
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| 199 Apache Spark and Apache Flink.en_US.srt |
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| 201 Section Overview.en_US.srt |
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| 202 Deep Learning and Unstructured Data.en_US.srt |
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| 202 Deep Learning and Unstructured Data.mp4 |
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| 203 Setting Up With Google.html |
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| 204 End-to-end-Dog-Vision-Notebook-the-project-well-be-working-through-.txt |
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| 204 Google-Colab-IO-example-how-to-get-data-in-and-out-of-your-Colab-notebook-.txt |
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| 204 Introduction-to-Google-Colab-example-notebook.txt |
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| 204 Kaggle-Dog-Breed-Identification-Competition-the-basis-of-our-upcoming-project-.txt |
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| 204 Setting Up Google Colab.en_US.srt |
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| 205 Google-Colab-FAQ-things-you-should-know-about-Google-Colab-.txt |
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| 206 Google-Colab-IO-example-how-to-get-data-in-and-out-of-your-Colab-notebook-.txt |
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| 206 Kaggle-Dog-Breed-Identification-Competition-Data.txt |
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| 206 Uploading Project Data.en_US.srt |
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| 207 Setting Up Our Data.en_US.srt |
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| 208 Setting Up Our Data 2.en_US.srt |
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| 209 Importing TensorFlow 2.en_US.srt |
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| 210 Loading-TensorFlow-2.0-into-a-Colab-Notebook-if-it-isnt-the-default-.txt |
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| 211 Google-Colab-example-GPU-usage.txt |
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| 211 Using A GPU.en_US.srt |
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| 212 Google-Colab-Example-of-GPU-speed-up-versus-CPU.txt |
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| 212 Introduction-to-Google-Colab-example-notebook.txt |
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| 213 Optional_ Reloading Colab Notebook.en_US.srt |
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| 214 Documentation-on-how-many-images-Google-recommends-for-image-problems.txt |
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| 214 Loading Our Data Labels.en_US.srt |
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| 215 Preparing The Images.en_US.srt |
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| 216 Turning Data Labels Into Numbers.en_US.srt |
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| 217 Blog-post-by-Rachel-Thomas-of-fast.ai-on-how-and-why-you-should-create-a-validation-set.txt |
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| 217 Creating Our Own Validation Set.en_US.srt |
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| 218 Documentation-for-loading-images-in-TensorFlow.txt |
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| 218 Preprocess Images.en_US.srt |
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| 218 TensorFlow-guidelines-for-loading-all-kinds-of-data-turning-your-data-into-Tensors-.txt |
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| 219 Preprocess Images 2.en_US.srt |
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| 220 Turning Data Into Batches.en_US.srt |
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| 221 Turning Data Into Batches 2.en_US.srt |
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| 221 Yann-LeCuns-OG-of-deep-learning-Tweet-on-Batch-Sizes.txt |
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| 222 Visualizing Our Data.en_US.srt |
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| 222 Visualizing Our Data.mp4 |
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| 223 Preparing Our Inputs and Outputs.en_US.srt |
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| 223 Preparing Our Inputs and Outputs.mp4 |
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| 223 TensorFlow-Hub-resource-for-pre-trained-deep-learning-models-and-more-.txt |
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| 224 Optional_ How machines learn and what's going on behind the scenes_.html |
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| 225 Andrei-Karpathys-talk-on-AI-at-Tesla.txt |
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| 225 Building A Deep Learning Model.en_US.srt |
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| 225 Building A Deep Learning Model.mp4 |
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| 225 MobileNetV2-the-model-were-using-on-TensorFlow-Hub.txt |
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| 225 Papers-with-Code-a-great-resource-for-some-of-the-best-machine-learning-papers-with-code-examples-.txt |
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| 225 PyTorch-Hub-PyTorch-version-of-TensorFlow-Hub-.txt |
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| 226 Building A Deep Learning Model 2.en_US.srt |
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| 226 Keras-in-TensorFlow-Overview-Documentation.txt |
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| 227 MobileNetV2-the-model-were-using-architecture-explanation-by-Sik-Ho-Tsang.txt |
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| 227 Step-by-step-breakdown-of-a-convolutional-neural-network-what-MobileNetV2-is-made-of-.txt |
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| 227 The-Softmax-Function-activation-function-we-use-in-our-model-.txt |
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| 228 -Article-How-to-choose-loss-activation-functions-when-building-a-deep-learning-model.txt |
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| 228 Building A Deep Learning Model 4.en_US.srt |
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| 228 Building A Deep Learning Model 4.mp4 |
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| 229 Summarizing Our Model.en_US.srt |
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| 230 Evaluating Our Model.en_US.srt |
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| 230 Evaluating Our Model.mp4 |
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| 230 TensorBoard-Callback-Documentation.txt |
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| 231 Early-Stopping-Callback-a-way-to-stop-your-model-from-training-when-it-stops-improving-Documentation.txt |
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| 231 Preventing Overfitting.en_US.srt |
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| 231 Preventing Overfitting.mp4 |
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| 232 Training Your Deep Neural Network.en_US.srt |
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| 232 Training Your Deep Neural Network.mp4 |
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| 233 Evaluating Performance With TensorBoard.en_US.srt |
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| 234 Make And Transform Predictions.en_US.srt |
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| 234 Make And Transform Predictions.mp4 |
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| 235 TensorFlow-documentation-for-the-unbatch-function.txt |
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| 235 Transform Predictions To Text.en_US.srt |
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| 236 Visualizing Model Predictions.en_US.srt |
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| 237 Visualizing And Evaluate Model Predictions 2.en_US.srt |
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| 238 Visualizing And Evaluate Model Predictions 3.en_US.srt |
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| 239 Saving And Loading A Trained Model.en_US.srt |
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| 240 Training Model On Full Dataset.en_US.srt |
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| 241 Dog-Vision-Prediction-Probabilities-Array.txt |
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| 241 Making Predictions On Test Images.en_US.srt |
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| 241 Making Predictions On Test Images.mp4 |
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| 242 Dog-Vision-Predictions-with-MobileNetV2-Ready-for-Kaggle-Submission.txt |
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| 242 Submitting Model to Kaggle.en_US.srt |
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| 242 Submitting Model to Kaggle.mp4 |
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| 243 End-to-end-Dog-Vision-Notebook-from-the-videos-.txt |
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| 243 End-to-end-Dog-Vision-Notebook-with-annotations-.txt |
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| 243 Making Predictions On Our Images.en_US.srt |
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| 243 Making Predictions On Our Images.mp4 |
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| 244 Finishing Dog Vision_ Where to next_.html |
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| 245 Section Overview.en_US.srt |
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| 245 Section Overview.mp4 |
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| 246 Communicating Your Work.en_US.srt |
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| 246 How-to-Think-About-Communicating-and-Sharing-Your-Work-blog-post-.txt |
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| 250 Communicating With Outside World.en_US.srt |
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| 250 Devblog-by-Hashnode-an-easy-and-free-way-to-create-a-blog-you-own-.txt |
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| 250 fast-template-by-fast.ai-a-template-you-can-use-for-your-blog-on-GitHub-Pages-.txt |
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| 251 Storytelling.en_US.srt |
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| 252 Communicating and sharing your work_ Further reading.html |
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| 253 Endorsements On LinkedIn.html |
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| 254 Quick Note_ Upcoming Video.html |
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| 255 What If I Don't Have Enough Experience_.en_US.srt |
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| 255 What If I Don't Have Enough Experience_.mp4 |
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| 256 Learning Guideline.html |
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| 265 Coding Challenges.html |
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| 267 What Is A Programming Language.en_US.srt |
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| 275 How To Succeed.html |
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| 294 Exercise_ Type Conversion.en_US.srt |
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| 294 Exercise_ Type Conversion.mp4 |
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| 295 DEVELOPER FUNDAMENTALS_ II.en_US.srt |
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| 295 DEVELOPER FUNDAMENTALS_ II.mp4 |
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| 295 Python-Comments-Best-Practices.txt |
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| 296 Exercise_ Password Checker.en_US.srt |
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| 296 Exercise_ Password Checker.mp4 |
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| 297 Lists.en_US.srt |
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| 297 Lists.mp4 |
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| 298 Exercise-Repl.txt |
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| 298 List Slicing.en_US.srt |
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| 298 List Slicing.mp4 |
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| 299 Exercise-Repl.txt |
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| 299 Matrix.en_US.srt |
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| 299 Matrix.mp4 |
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| 300 List Methods.en_US.srt |
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| 300 List Methods.mp4 |
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| 300 List-Methods.txt |
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| 301 Exercise-Repl.txt |
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| 301 List Methods 2.en_US.srt |
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| 301 List Methods 2.mp4 |
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| 301 Python-Keywords.txt |
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| 302 List Methods 3.en_US.srt |
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| 302 List Methods 3.mp4 |
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| 303 Common List Patterns.en_US.srt |
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| 303 Common List Patterns.mp4 |
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| 303 Exercise-Repl.txt |
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| 304 List Unpacking.en_US.srt |
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| 304 List Unpacking.mp4 |
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| 305 None.en_US.srt |
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| 306 Dictionaries.en_US.srt |
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| 306 Dictionaries.mp4 |
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| 307 DEVELOPER FUNDAMENTALS_ III.en_US.srt |
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| 307 DEVELOPER FUNDAMENTALS_ III.mp4 |
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| 308 Dictionary Keys.en_US.srt |
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| 309 Dictionary Methods.en_US.srt |
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| 310 Exercise-Repl.txt |
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| 311 Tuples.en_US.srt |
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| 312 Tuple-Methods.txt |
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| 313 Sets.en_US.srt |
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| 314 Exercise-Repl.txt |
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| 314 Sets-Methods.txt |
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| 315 Breaking The Flow.en_US.srt |
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| 315 Breaking The Flow.mp4 |
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| 316 Conditional Logic.en_US.srt |
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| 316 Conditional Logic.mp4 |
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| 317 Indentation In Python.en_US.srt |
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| 317 Indentation In Python.mp4 |
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| 318 Truthy vs Falsey.en_US.srt |
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| 318 Truthy vs Falsey.mp4 |
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| 318 Truthy-vs-Falsey-Stackoverflow.txt |
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| 319 Ternary Operator.en_US.srt |
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| 319 Ternary Operator.mp4 |
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| 320 Short Circuiting.en_US.srt |
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| 321 Logical Operators.en_US.srt |
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| 322 Exercise_ Logical Operators.en_US.srt |
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| 322 Exercise_ Logical Operators.mp4 |
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| 323 is vs ==.en_US.srt |
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| 324 For Loops.en_US.srt |
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| 326 Exercise_ Tricky Counter.en_US.srt |
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| 326 Exercise_ Tricky Counter.mp4 |
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| 326 Solution-Repl.txt |
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| 332 Exercise-Repl.txt |
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| 332 Our First GUI.en_US.srt |
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| 332 Solution-Repl.txt |
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| 333 DEVELOPER FUNDAMENTALS_ IV.en_US.srt |
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| 333 DEVELOPER FUNDAMENTALS_ IV.mp4 |
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| 334 Exercise_ Find Duplicates.en_US.srt |
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| 334 Exercise_ Find Duplicates.mp4 |
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| 334 Solution-Repl.txt |
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| 335 Functions.en_US.srt |
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| 335 Functions.mp4 |
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| 336 Parameters and Arguments.en_US.srt |
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| 336 Parameters and Arguments.mp4 |
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| 338 return.en_US.srt |
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| 339 Exercise_ Tesla.html |
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| 340 Methods vs Functions.en_US.srt |
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| 341 Docstrings.en_US.srt |
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| 342 Clean Code.en_US.srt |
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| 343 _args and __kwargs.en_US.srt |
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| 343 _args and __kwargs.mp4 |
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| 344 Exercise_ Functions.en_US.srt |
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| 344 Solution-Repl.txt |
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| 345 Scope.en_US.srt |
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| 346 Scope Rules.en_US.srt |
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| 347 global Keyword.en_US.srt |
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| 348 nonlocal Keyword.en_US.srt |
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| 348 nonlocal Keyword.mp4 |
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| 348 Solution-Repl.txt |
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| 349 Why Do We Need Scope_.en_US.srt |
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| 349 Why Do We Need Scope_.mp4 |
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| 350 Pure Functions.en_US.srt |
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| 351 map().en_US.srt |
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| 355 List Comprehensions.en_US.srt |
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| 356 Set Comprehensions.en_US.srt |
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| 357 Exercise_ Comprehensions.en_US.srt |
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| 358 Python Exam_ Testing Your Understanding.html |
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| 359 Modules in Python.en_US.srt |
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| 359 Modules in Python.mp4 |
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| 360 Quick Note_ Upcoming Videos.html |
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| 361 Optional_ PyCharm.en_US.srt |
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| 361 Optional_ PyCharm.mp4 |
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| 362 Packages in Python.en_US.srt |
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| 362 Packages in Python.mp4 |
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| 363 Different Ways To Import.en_US.srt |
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| 363 Different Ways To Import.mp4 |
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| 364 Next Steps.html |
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| 365 Statistics and Mathematics.html |
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| 366 Become An Alumni.html |
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| 367 Thank You.en_US.srt |
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| 367 Thank You.mp4 |
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| 368 Bonus_ Special Thank You Gift!.html |
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