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| 001 AI, Machine Learning and Deep Learning.en.srt |
5.69Кб |
| 001 AI, Machine Learning and Deep Learning.mp4 |
16.23Мб |
| 001 BONUS.html |
30.16Кб |
| 001 Data Frame Attributes and Methods Part – I.en.srt |
16.16Кб |
| 001 Data Frame Attributes and Methods Part – I.mp4 |
79.75Мб |
| 001 Data Types in Python.en.srt |
14.07Кб |
| 001 Data Types in Python.mp4 |
41.08Мб |
| 001 Data Visualization with Python Masterclass.en.srt |
3.67Кб |
| 001 Data Visualization with Python Masterclass.mp4 |
17.88Мб |
| 001 Installing Anaconda Distribution and Python.en.srt |
4.79Кб |
| 001 Installing Anaconda Distribution and Python.mp4 |
37.54Мб |
| 001 Introduction to Deep Learning with Python.en.srt |
5.88Кб |
| 001 Introduction to Deep Learning with Python.mp4 |
14.51Мб |
| 001 Logic of OOP.en.srt |
5.30Кб |
| 001 Logic of OOP.mp4 |
16.38Мб |
| 001 Project - 1.en.srt |
20.90Кб |
| 001 Project - 1.mp4 |
101.56Мб |
| 001 Understanding RNN and LSTM Networks.en.srt |
15.14Кб |
| 001 Understanding RNN and LSTM Networks.mp4 |
50.85Мб |
| 001 What is Artificial Neural Network (ANN)_.en.srt |
8.40Кб |
| 001 What is Artificial Neural Network (ANN)_.mp4 |
23.01Мб |
| 001 What is CNN_.en.srt |
17.86Кб |
| 001 What is CNN_.mp4 |
72.43Мб |
| 001 What is Geoplotlib_.en.srt |
10.58Кб |
| 001 What is Geoplotlib_.mp4 |
32.21Мб |
| 001 What is Numpy_.en.srt |
7.64Кб |
| 001 What is Numpy_.mp4 |
26.74Мб |
| 001 What is Pandas_.en.srt |
6.54Кб |
| 001 What is Pandas_.mp4 |
22.32Мб |
| 001 What is Seaborn_.en.srt |
5.20Кб |
| 001 What is Seaborn_.mp4 |
12.89Мб |
| 001 What is Transfer Learning.en.srt |
19.43Кб |
| 001 What is Transfer Learning.mp4 |
85.32Мб |
| 002 Anatomy of Neural Network.en.srt |
10.74Кб |
| 002 Anatomy of Neural Network.mp4 |
42.28Мб |
| 002 Constructor.en.srt |
7.16Кб |
| 002 Constructor.mp4 |
33.89Мб |
| 002 Controlling Figure Aesthetics.en.srt |
11.19Кб |
| 002 Controlling Figure Aesthetics.mp4 |
39.19Мб |
| 002 Data Frame attributes and Methods Part – II.en.srt |
11.88Кб |
| 002 Data Frame attributes and Methods Part – II.mp4 |
56.97Мб |
| 002 Example - 1.en.srt |
9.95Кб |
| 002 Example - 1.mp4 |
36.40Мб |
| 002 History of Machine Learning.en.srt |
8.05Кб |
| 002 History of Machine Learning.mp4 |
23.85Мб |
| 002 Operators in Python.en.srt |
11.06Кб |
| 002 Operators in Python.mp4 |
29.62Мб |
| 002 Overview of Jupyter Notebook and Google Colab.en.srt |
5.95Кб |
| 002 Overview of Jupyter Notebook and Google Colab.mp4 |
25.37Мб |
| 002 Project - 2.en.srt |
21.62Кб |
| 002 Project - 2.mp4 |
169.25Мб |
| 002 Project Files and Course Documents.html |
1.17Кб |
| 002 Series and Features.en.srt |
19.46Кб |
| 002 Series and Features.mp4 |
83.55Мб |
| 002 Using Matplotlib.en.srt |
7.85Кб |
| 002 Using Matplotlib.mp4 |
26.53Мб |
| 002 Why Numpy_.en.srt |
5.05Кб |
| 002 Why Numpy_.mp4 |
13.64Мб |
| 003 Array and features.en.srt |
11.94Кб |
| 003 Array and features.mp4 |
47.91Мб |
| 003 Conditionals.en.srt |
10.03Кб |
| 003 Conditionals.mp4 |
34.63Мб |
| 003 Creating a Simple ANN.en.srt |
15.10Кб |
| 003 Creating a Simple ANN.mp4 |
79.48Мб |
| 003 Data Frame attributes and Methods Part – III.en.srt |
9.79Кб |
| 003 Data Frame attributes and Methods Part – III.mp4 |
48.05Мб |
| 003 Example.en.srt |
10.01Кб |
| 003 Example.mp4 |
51.32Мб |
| 003 Example - 2.en.srt |
19.26Кб |
| 003 Example - 2.mp4 |
76.27Мб |
| 003 Methods.en.srt |
4.30Кб |
| 003 Methods.mp4 |
23.64Мб |
| 003 Project - 3.en.srt |
15.51Кб |
| 003 Project - 3.mp4 |
82.34Мб |
| 003 Pyplot – Pylab - Matplotlib.en.srt |
7.54Кб |
| 003 Pyplot – Pylab - Matplotlib.mp4 |
26.60Мб |
| 003 Turing Machine and Turing Test.en.srt |
13.79Кб |
| 003 Turing Machine and Turing Test.mp4 |
40.90Мб |
| 004 Array’s Operators.en.srt |
4.36Кб |
| 004 Array’s Operators.mp4 |
17.58Мб |
| 004 Color Palettes.en.srt |
15.12Кб |
| 004 Color Palettes.mp4 |
45.42Мб |
| 004 Example - 3.en.srt |
11.78Кб |
| 004 Example - 3.mp4 |
47.81Мб |
| 004 Figure, Subplot and Axes.en.srt |
18.19Кб |
| 004 Figure, Subplot and Axes.mp4 |
65.66Мб |
| 004 Inheritance.en.srt |
7.02Кб |
| 004 Inheritance.mp4 |
32.63Мб |
| 004 Loops.en.srt |
12.43Кб |
| 004 Loops.mp4 |
49.10Мб |
| 004 Multi index.en.srt |
12.49Кб |
| 004 Multi index.mp4 |
50.80Мб |
| 004 Project - 4.en.srt |
15.20Кб |
| 004 Project - 4.mp4 |
72.26Мб |
| 004 Tensor Operations.en.srt |
11.38Кб |
| 004 Tensor Operations.mp4 |
62.12Мб |
| 004 What is Deep Learning.en.srt |
7.38Кб |
| 004 What is Deep Learning.mp4 |
20.53Мб |
| 005 Basic Plots in Seaborn.mp4 |
92.79Мб |
| 005 Figure Customization.en.srt |
14.54Кб |
| 005 Figure Customization.mp4 |
59.06Мб |
| 005 Groupby Operations.en.srt |
12.81Кб |
| 005 Groupby Operations.mp4 |
52.59Мб |
| 005 Learning representations from data.en.srt |
13.93Кб |
| 005 Learning representations from data.mp4 |
34.90Мб |
| 005 Lists, Tuples, Dictionaries and Sets.en.srt |
18.21Кб |
| 005 Lists, Tuples, Dictionaries and Sets.mp4 |
66.35Мб |
| 005 Numpy Functions.en.srt |
19.86Кб |
| 005 Numpy Functions.mp4 |
78.52Мб |
| 005 Overriding and Overloading.en.srt |
9.74Кб |
| 005 Overriding and Overloading.mp4 |
58.82Мб |
| 005 Tensor Operations 2.en.srt |
8.26Кб |
| 005 Tensor Operations 2.mp4 |
29.78Мб |
| 006 Data Type Operators and Methods.en.srt |
9.31Кб |
| 006 Data Type Operators and Methods.mp4 |
40.46Мб |
| 006 Indexing and Slicing.en.srt |
8.99Кб |
| 006 Indexing and Slicing.mp4 |
40.39Мб |
| 006 Keras API.en.srt |
8.26Кб |
| 006 Keras API.mp4 |
23.30Мб |
| 006 Missing Data and Data Munging Part I.en.srt |
22.86Кб |
| 006 Missing Data and Data Munging Part I.mp4 |
79.35Мб |
| 006 Multi-Plots in Seaborn.en.srt |
11.08Кб |
| 006 Multi-Plots in Seaborn.mp4 |
40.94Мб |
| 006 Plot Customization.en.srt |
6.90Кб |
| 006 Plot Customization.mp4 |
25.75Мб |
| 006 Workflow of Machine Learning.en.srt |
11.15Кб |
| 006 Workflow of Machine Learning.mp4 |
31.67Мб |
| 007 Grid, Spines, Ticks.en.srt |
8.48Кб |
| 007 Grid, Spines, Ticks.mp4 |
22.39Мб |
| 007 Machine Learning Methods.en.srt |
16.62Кб |
| 007 Machine Learning Methods.mp4 |
45.55Мб |
| 007 Missing Data and Data Munging Part II.en.srt |
11.23Кб |
| 007 Missing Data and Data Munging Part II.mp4 |
40.79Мб |
| 007 Modules in Python.en.srt |
5.53Кб |
| 007 Modules in Python.mp4 |
21.06Мб |
| 007 Numpy Exercises.en.srt |
15.41Кб |
| 007 Numpy Exercises.mp4 |
74.18Мб |
| 007 Optimizers.en.srt |
12.44Кб |
| 007 Optimizers.mp4 |
42.32Мб |
| 007 Regression Plots and Squarify.en.srt |
16.11Кб |
| 007 Regression Plots and Squarify.mp4 |
56.50Мб |
| 008 Basic Plots in Matplotlib I.en.srt |
31.55Кб |
| 008 Basic Plots in Matplotlib I.mp4 |
104.40Мб |
| 008 Dealing with Missing Data.en.srt |
16.28Кб |
| 008 Dealing with Missing Data.mp4 |
69.23Мб |
| 008 Functions in Python.en.srt |
9.29Кб |
| 008 Functions in Python.mp4 |
26.06Мб |
| 008 Supervised Machine Learning Methods - 1.en.srt |
10.75Кб |
| 008 Supervised Machine Learning Methods - 1.mp4 |
30.94Мб |
| 008 Using Numpy in Linear Algebra.en.srt |
31.85Кб |
| 008 Using Numpy in Linear Algebra.mp4 |
112.16Мб |
| 008 Using Numpy in Linear Algebra.mp4.vtx |
442.50Кб |
| 008 What is TensorFlow.en.srt |
20.79Кб |
| 008 What is TensorFlow.mp4 |
62.61Мб |
| 009 Basic Plots in Matplotlib II.en.srt |
16.24Кб |
| 009 Basic Plots in Matplotlib II.mp4 |
51.52Мб |
| 009 Combining Data Frames Part – I.en.srt |
18.01Кб |
| 009 Combining Data Frames Part – I.mp4 |
103.55Мб |
| 009 Exercise Analyse.en.srt |
2.26Кб |
| 009 Exercise Analyse.mp4 |
5.70Мб |
| 009 NumExpr Guide.en.srt |
8.00Кб |
| 009 NumExpr Guide.mp4 |
42.19Мб |
| 009 Supervised Machine Learning Methods - 2.en.srt |
15.80Кб |
| 009 Supervised Machine Learning Methods - 2.mp4 |
55.36Мб |
| 010 Combining Data Frames Part – II.en.srt |
18.13Кб |
| 010 Combining Data Frames Part – II.mp4 |
84.17Мб |
| 010 Exercise Solution.en.srt |
6.65Кб |
| 010 Exercise Solution.mp4 |
47.69Мб |
| 010 Supervised Machine Learning Methods - 3.en.srt |
16.38Кб |
| 010 Supervised Machine Learning Methods - 3.mp4 |
56.07Мб |
| 011 Supervised Machine Learning Methods - 4.en.srt |
19.46Кб |
| 011 Supervised Machine Learning Methods - 4.mp4 |
70.31Мб |
| 011 Work with Dataset Files.en.srt |
12.09Кб |
| 011 Work with Dataset Files.mp4 |
70.73Мб |
| 012 Unsupervised Machine Learning Methods.en.srt |
27.60Кб |
| 012 Unsupervised Machine Learning Methods.mp4 |
87.94Мб |
| 013 Gathering data.en.srt |
5.86Кб |
| 013 Gathering data.mp4 |
17.61Мб |
| 014 Data pre-processing.en.srt |
6.51Кб |
| 014 Data pre-processing.mp4 |
25.97Мб |
| 015 Choosing the right algorithm and model.en.srt |
9.21Кб |
| 015 Choosing the right algorithm and model.mp4 |
148.96Мб |
| 016 Training and testing the model.en.srt |
6.48Кб |
| 016 Training and testing the model.mp4 |
83.89Мб |
| 017 Evaluation.en.srt |
7.67Кб |
| 017 Evaluation.mp4 |
24.37Мб |
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| TutsNode.com.txt |
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