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[GigaCourse.Com].url |
49б |
[GigaCourse.Com].url |
49б |
[GigaCourse.Com].url |
49б |
[GigaCourse.Com].url |
49б |
[GigaCourse.Com].url |
49б |
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 |