[UdemyCourseDownloader] Deep Learning with TensorFlow 2.0 [2019] torrent, magnet, bt

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[UdemyCourseDownloader] Deep Learning with TensorFlow 2.0 [2019]

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UdemyCourseDownloader Deep Learning with TensorFlow 2019

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Size

14. Appendix Linear Algebra Fundamentals/11. Why is Linear Algebra Useful.mp4

144.34MB

udemycoursedownloader.com.url

132B

01. Welcome! Course introduction/1. Meet your instructors and why you should study machine learning.mp4

105.79MB

01. Welcome! Course introduction/1. Meet your instructors and why you should study machine learning.vtt

8.82KB

01. Welcome! Course introduction/2. What does the course cover.mp4

16.36MB

01. Welcome! Course introduction/2. What does the course cover.vtt

5.47KB

01. Welcome! Course introduction/3. What does the course cover - Quiz.html

161B

02. Introduction to neural networks/1. Introduction to neural networks.mp4

13.56MB

02. Introduction to neural networks/1. Introduction to neural networks.vtt

5.19KB

02. Introduction to neural networks/1.1 Course Notes - Section 2.pdf.pdf

927.67KB

02. Introduction to neural networks/2. Introduction to neural networks - Quiz.html

161B

02. Introduction to neural networks/3. Training the model.mp4

8.82MB

02. Introduction to neural networks/3. Training the model.vtt

3.81KB

02. Introduction to neural networks/3.1 Course Notes - Section 2.pdf.pdf

927.67KB

02. Introduction to neural networks/4. Training the model - Quiz.html

161B

02. Introduction to neural networks/5. Types of machine learning.mp4

12.2MB

02. Introduction to neural networks/5. Types of machine learning.vtt

4.64KB

02. Introduction to neural networks/5.1 Course Notes - Section 2.pdf.pdf

927.67KB

02. Introduction to neural networks/6. Types of machine learning - Quiz.html

161B

02. Introduction to neural networks/7. The linear model.mp4

9.13MB

02. Introduction to neural networks/7. The linear model.vtt

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02. Introduction to neural networks/7.1 Course Notes - Section 2.pdf.pdf

927.67KB

02. Introduction to neural networks/8. The linear model - Quiz.html

161B

02. Introduction to neural networks/9. Need Help with Linear Algebra.html

829B

02. Introduction to neural networks/10. The linear model. Multiple inputs.mp4

7.5MB

02. Introduction to neural networks/10. The linear model. Multiple inputs.vtt

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02. Introduction to neural networks/10.1 Course Notes - Section 2.pdf.pdf

927.67KB

02. Introduction to neural networks/11. The linear model. Multiple inputs - Quiz.html

161B

02. Introduction to neural networks/12. The linear model. Multiple inputs and multiple outputs.mp4

38.29MB

02. Introduction to neural networks/12. The linear model. Multiple inputs and multiple outputs.vtt

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02. Introduction to neural networks/12.1 Course Notes - Section 2.pdf.pdf

927.67KB

02. Introduction to neural networks/13. The linear model. Multiple inputs and multiple outputs - Quiz.html

161B

02. Introduction to neural networks/14. Graphical representation.mp4

6.35MB

02. Introduction to neural networks/14. Graphical representation.vtt

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02. Introduction to neural networks/14.1 Course Notes - Section 2.pdf.pdf

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02. Introduction to neural networks/15. Graphical representation - Quiz.html

161B

02. Introduction to neural networks/16. The objective function.mp4

5.72MB

02. Introduction to neural networks/16. The objective function.vtt

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02. Introduction to neural networks/16.1 Course Notes - Section 2.pdf.pdf

927.67KB

02. Introduction to neural networks/17. The objective function - Quiz.html

161B

02. Introduction to neural networks/18. L2-norm loss.mp4

7.26MB

02. Introduction to neural networks/18. L2-norm loss.vtt

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02. Introduction to neural networks/18.1 Course Notes - Section 2.pdf.pdf

927.67KB

02. Introduction to neural networks/19. L2-norm loss - Quiz.html

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02. Introduction to neural networks/20. Cross-entropy loss.mp4

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02. Introduction to neural networks/20. Cross-entropy loss.vtt

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02. Introduction to neural networks/20.1 Course Notes - Section 2.pdf.pdf

927.67KB

02. Introduction to neural networks/21. Cross-entropy loss - Quiz.html

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02. Introduction to neural networks/22. One parameter gradient descent.mp4

17.77MB

02. Introduction to neural networks/22. One parameter gradient descent.vtt

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02. Introduction to neural networks/22.1 Course Notes - Section 2.pdf.pdf

927.67KB

02. Introduction to neural networks/22.2 GD-function-example.xlsx.xlsx

42.33KB

02. Introduction to neural networks/23. One parameter gradient descent - Quiz.html

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02. Introduction to neural networks/24. N-parameter gradient descent.mp4

39.45MB

02. Introduction to neural networks/24. N-parameter gradient descent.vtt

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02. Introduction to neural networks/24.1 Course Notes - Section 2.pdf.pdf

927.67KB

02. Introduction to neural networks/25. N-parameter gradient descent - Quiz.html

161B

03. Setting up the working environment/1. Setting up the environment - An introduction - Do not skip, please!.mp4

7.18MB

03. Setting up the working environment/1. Setting up the environment - An introduction - Do not skip, please!.vtt

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03. Setting up the working environment/2. Why Python and why Jupyter.mp4

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03. Setting up the working environment/2. Why Python and why Jupyter.vtt

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03. Setting up the working environment/3. Why Python and why Jupyter - Quiz.html

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03. Setting up the working environment/4. Installing Anaconda.mp4

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03. Setting up the working environment/4. Installing Anaconda.vtt

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03. Setting up the working environment/5. The Jupyter dashboard - part 1.mp4

9.5MB

03. Setting up the working environment/5. The Jupyter dashboard - part 1.vtt

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03. Setting up the working environment/6. The Jupyter dashboard - part 2.mp4

21.08MB

03. Setting up the working environment/6. The Jupyter dashboard - part 2.vtt

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03. Setting up the working environment/7. Jupyter Shortcuts.html

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03. Setting up the working environment/7.1 Shortcuts for Jupyter.pdf.pdf

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03. Setting up the working environment/8. The Jupyter dashboard - Quiz.html

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03. Setting up the working environment/9. Installing TensorFlow 2.mp4

42.94MB

03. Setting up the working environment/9. Installing TensorFlow 2.vtt

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03. Setting up the working environment/10. Installing packages - exercise.html

227B

03. Setting up the working environment/11. Installing packages - solution.html

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04. Minimal example - your first machine learning algorithm/1. Minimal example - part 1.mp4

6.53MB

04. Minimal example - your first machine learning algorithm/1. Minimal example - part 1.vtt

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04. Minimal example - your first machine learning algorithm/1.1 Minimal example Part 1.html

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04. Minimal example - your first machine learning algorithm/2. Minimal example - part 2.mp4

10.71MB

04. Minimal example - your first machine learning algorithm/2. Minimal example - part 2.vtt

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04. Minimal example - your first machine learning algorithm/2.1 Minimal example - part 2.html

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04. Minimal example - your first machine learning algorithm/3. Minimal example - part 3.mp4

9.77MB

04. Minimal example - your first machine learning algorithm/3. Minimal example - part 3.vtt

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04. Minimal example - your first machine learning algorithm/3.1 Minimal example - part 3.html

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04. Minimal example - your first machine learning algorithm/4. Minimal example - part 4.mp4

20.81MB

04. Minimal example - your first machine learning algorithm/4. Minimal example - part 4.vtt

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04. Minimal example - your first machine learning algorithm/4.1 Minimal example - part 4.html

145B

04. Minimal example - your first machine learning algorithm/5. Minimal example - Exercises.html

1.57KB

04. Minimal example - your first machine learning algorithm/5.1 Minimal_example_All_Exercises.html

143B

04. Minimal example - your first machine learning algorithm/5.2 Minimal_example_Exercise_1_Solution.html

149B

04. Minimal example - your first machine learning algorithm/5.3 Minimal_example_Exercise_5_Solution.html

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04. Minimal example - your first machine learning algorithm/5.4 Minimal_example_Exercise_2_Solution.html

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04. Minimal example - your first machine learning algorithm/5.5 Minimal_example_Exercise_4_Solution.html

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04. Minimal example - your first machine learning algorithm/5.6 Minimal_example_Exercise_6_Solution.html

149B

04. Minimal example - your first machine learning algorithm/5.7 Minimal_example_Exercise_3.d. Solution.html

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04. Minimal example - your first machine learning algorithm/5.8 Minimal_example_Exercise_3.b. Solution.html

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04. Minimal example - your first machine learning algorithm/5.9 Minimal_example_Exercise_3.a. Solution.html

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04. Minimal example - your first machine learning algorithm/5.10 Minimal_example_Exercise_3.c. Solution.html

154B

05. TensorFlow - An introduction/1. TensorFlow outline.mp4

38.32MB

05. TensorFlow - An introduction/1. TensorFlow outline.vtt

4.61KB

05. TensorFlow - An introduction/2. TensorFlow 2 intro.mp4

25.07MB

05. TensorFlow - An introduction/2. TensorFlow 2 intro.vtt

3.22KB

05. TensorFlow - An introduction/3. A Note on Coding in TensorFlow.mp4

7.13MB

05. TensorFlow - An introduction/3. A Note on Coding in TensorFlow.vtt

1.22KB

05. TensorFlow - An introduction/4. Types of file formats in TensorFlow and data handling.mp4

18.5MB

05. TensorFlow - An introduction/4. Types of file formats in TensorFlow and data handling.vtt

3.04KB

05. TensorFlow - An introduction/4.1 TensorFlow Minimal Example - Part 1.html

146B

05. TensorFlow - An introduction/5. Model layout - inputs, outputs, targets, weights, biases, optimizer and loss.mp4

38.22MB

05. TensorFlow - An introduction/5. Model layout - inputs, outputs, targets, weights, biases, optimizer and loss.vtt

6.87KB

05. TensorFlow - An introduction/5.1 TensorFlow Minimal Example - Part 2.html

146B

05. TensorFlow - An introduction/6. Interpreting the result and extracting the weights and bias.mp4

32.82MB

05. TensorFlow - An introduction/6. Interpreting the result and extracting the weights and bias.vtt

5.43KB

05. TensorFlow - An introduction/6.1 TensorFlow Minimal Example - Part 3.html

146B

05. TensorFlow - An introduction/7. Cutomizing your model.mp4

24.66MB

05. TensorFlow - An introduction/7. Cutomizing your model.vtt

3.6KB

05. TensorFlow - An introduction/7.1 TensorFlow Minimal Example - Complete Code with Comments.html

163B

05. TensorFlow - An introduction/7.2 TensorFlow Minimal Example - Complete Code.html

149B

05. TensorFlow - An introduction/8. Minimal example - Exercises.html

1.35KB

05. TensorFlow - An introduction/8.1 TensorFlow Minimal Example - Exercise 3 - Solution.html

160B

05. TensorFlow - An introduction/8.2 TensorFlow Minimal Example - Exercise 1 - Solution.html

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05. TensorFlow - An introduction/8.3 TensorFlow Minimal Example - Exercise 2_1 - Solution.html

162B

05. TensorFlow - An introduction/8.4 TensorFlow Minimal Example - All Exercises.html

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05. TensorFlow - An introduction/8.5 TensorFlow Minimal Example - Exercise 2_2 - Solution.html

162B

06. Going deeper Introduction to deep neural networks/1. Layers.mp4

4.74MB

06. Going deeper Introduction to deep neural networks/1. Layers.vtt

2.15KB

06. Going deeper Introduction to deep neural networks/1.1 Course Notes - Section 6.pdf.pdf

936.42KB

06. Going deeper Introduction to deep neural networks/2. What is a deep net.mp4

6.73MB

06. Going deeper Introduction to deep neural networks/2. What is a deep net.vtt

2.87KB

06. Going deeper Introduction to deep neural networks/2.1 Course Notes - Section 6.pdf.pdf

936.42KB

06. Going deeper Introduction to deep neural networks/3. Understanding deep nets in depth.mp4

13.41MB

06. Going deeper Introduction to deep neural networks/3. Understanding deep nets in depth.vtt

5.82KB

06. Going deeper Introduction to deep neural networks/4. Why do we need non-linearities.mp4

8.96MB

06. Going deeper Introduction to deep neural networks/4. Why do we need non-linearities.vtt

3.33KB

06. Going deeper Introduction to deep neural networks/5. Activation functions.mp4

8.74MB

06. Going deeper Introduction to deep neural networks/5. Activation functions.vtt

4.53KB

06. Going deeper Introduction to deep neural networks/6. Softmax activation.mp4

7.38MB

06. Going deeper Introduction to deep neural networks/6. Softmax activation.vtt

3.79KB

06. Going deeper Introduction to deep neural networks/7. Backpropagation.mp4

11.06MB

06. Going deeper Introduction to deep neural networks/7. Backpropagation.vtt

3.86KB

06. Going deeper Introduction to deep neural networks/8. Backpropagation - visual representation.mp4

6.85MB

06. Going deeper Introduction to deep neural networks/8. Backpropagation - visual representation.vtt

3.47KB

07. Backpropagation. A peek into the Mathematics of Optimization/1. Backpropagation. A peek into the Mathematics of Optimization.html

539B

07. Backpropagation. A peek into the Mathematics of Optimization/1.1 Backpropagation-a-peek-into-the-Mathematics-of-Optimization.pdf.pdf

182.36KB

08. Overfitting/1. Underfitting and overfitting.mp4

11.06MB

08. Overfitting/1. Underfitting and overfitting.vtt

4.96KB

08. Overfitting/2. Underfitting and overfitting - classification.mp4

6.77MB

08. Overfitting/2. Underfitting and overfitting - classification.vtt

2.36KB

08. Overfitting/3. Training and validation.mp4

9.23MB

08. Overfitting/3. Training and validation.vtt

4.25KB

08. Overfitting/4. Training, validation, and test.mp4

7.45MB

08. Overfitting/4. Training, validation, and test.vtt

3.08KB

08. Overfitting/5. N-fold cross validation.mp4

6.99MB

08. Overfitting/5. N-fold cross validation.vtt

3.7KB

08. Overfitting/6. Early stopping.mp4

9.44MB

08. Overfitting/6. Early stopping.vtt

6.01KB

09. Initialization/1. Initialization - Introduction.mp4

8.03MB

09. Initialization/1. Initialization - Introduction.vtt

3.12KB

09. Initialization/2. Types of simple initializations.mp4

5.61MB

09. Initialization/2. Types of simple initializations.vtt

3.23KB

09. Initialization/3. Xavier initialization.mp4

5.83MB

09. Initialization/3. Xavier initialization.vtt

3.25KB

10. Gradient descent and learning rates/1. Stochastic gradient descent.mp4

9.39MB

10. Gradient descent and learning rates/1. Stochastic gradient descent.vtt

4.23KB

10. Gradient descent and learning rates/2. Gradient descent pitfalls.mp4

4.31MB

10. Gradient descent and learning rates/2. Gradient descent pitfalls.vtt

2.5KB

10. Gradient descent and learning rates/3. Momentum.mp4

6.11MB

10. Gradient descent and learning rates/3. Momentum.vtt

3.1KB

10. Gradient descent and learning rates/4. Learning rate schedules.mp4

10.31MB

10. Gradient descent and learning rates/4. Learning rate schedules.vtt

5.25KB

10. Gradient descent and learning rates/5. Learning rate schedules. A picture.mp4

3.14MB

10. Gradient descent and learning rates/5. Learning rate schedules. A picture.vtt

1.9KB

10. Gradient descent and learning rates/6. Adaptive learning rate schedules.mp4

8.86MB

10. Gradient descent and learning rates/6. Adaptive learning rate schedules.vtt

4.57KB

10. Gradient descent and learning rates/7. Adaptive moment estimation.mp4

7.78MB

10. Gradient descent and learning rates/7. Adaptive moment estimation.vtt

2.93KB

11. Preprocessing/1. Preprocessing introduction.mp4

8.42MB

11. Preprocessing/1. Preprocessing introduction.vtt

3.38KB

11. Preprocessing/2. Basic preprocessing.mp4

3.65MB

11. Preprocessing/2. Basic preprocessing.vtt

1.48KB

11. Preprocessing/3. Standardization.mp4

8.33MB

11. Preprocessing/3. Standardization.vtt

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11. Preprocessing/4. Dealing with categorical data.mp4

6.08MB

11. Preprocessing/4. Dealing with categorical data.vtt

2.44KB

11. Preprocessing/5. One-hot and binary encoding.mp4

6.24MB

11. Preprocessing/5. One-hot and binary encoding.vtt

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12. The MNIST example/1. The dataset.mp4

15.67MB

12. The MNIST example/1. The dataset.vtt

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12. The MNIST example/2. How to tackle the MNIST.mp4

20.4MB

12. The MNIST example/2. How to tackle the MNIST.vtt

3.11KB

12. The MNIST example/3. Importing the relevant packages and load the data.mp4

17.77MB

12. The MNIST example/3. Importing the relevant packages and load the data.vtt

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12. The MNIST example/3.1 TensorFlow MNIST - Part 1 with comments.html

150B

12. The MNIST example/4. Preprocess the data - create a validation dataset and scale the data.mp4

31.94MB

12. The MNIST example/4. Preprocess the data - create a validation dataset and scale the data.vtt

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12. The MNIST example/5. Preprocess the data - scale the test data.html

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12. The MNIST example/5.1 TensorFlow MNIST - Part 2 with comments.html

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12. The MNIST example/6. Preprocess the data - shuffle and batch the data.mp4

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12. The MNIST example/6. Preprocess the data - shuffle and batch the data.vtt

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12. The MNIST example/7. Preprocess the data - shuffle and batch the data.html

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12. The MNIST example/7.1 TensorFlow MNIST - Part 3 with comments.html

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12. The MNIST example/8. Outline the model.mp4

31.17MB

12. The MNIST example/8. Outline the model.vtt

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12. The MNIST example/8.1 TensorFlow MNIST - Part 4 with comments.html

150B

12. The MNIST example/9. Select the loss and the optimizer.mp4

15.26MB

12. The MNIST example/9. Select the loss and the optimizer.vtt

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12. The MNIST example/9.1 TensorFlow MNIST - Part 5 with comments.html

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12. The MNIST example/10. Learning.mp4

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12. The MNIST example/10. Learning.vtt

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12. The MNIST example/10.1 TensorFlow MNIST - Part 6 with comments.html

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12. The MNIST example/11. MNIST - exercises.html

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12. The MNIST example/11.1 TensorFlow MNIST - All Exercises.html

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12. The MNIST example/12. MNIST - solutions.html

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12. The MNIST example/12.1 4. TensorFlow MNIST - Exercise 4 Solution.html

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12. The MNIST example/12.2 7. TensorFlow MNIST - Exercise 7 Solution.html

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12. The MNIST example/12.3 5. TensorFlow MNIST - Exercise 5 Solution.html

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12. The MNIST example/12.4 1. TensorFlow MNIST - Exercise 1 Solution.html

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12. The MNIST example/12.5 8. TensorFlow MNIST - Exercise 8 Solution.html

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12. The MNIST example/12.6 2. TensorFlow MNIST - Exercise 2 Solution.html

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12. The MNIST example/12.7 10. TensorFlow MNIST - Exercise 10 Solution.html

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12. The MNIST example/12.8 6. TensorFlow MNIST - Exercise 6 Solution.html

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12. The MNIST example/12.9 9. TensorFlow MNIST - Exercise 9 Solution.html

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12. The MNIST example/12.10 3. TensorFlow MNIST - Exercise 3 Solution.html

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12. The MNIST example/13. Testing the model.mp4

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12. The MNIST example/13. Testing the model.vtt

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12. The MNIST example/13.1 TensorFlow MNIST - Complete Code with Comments.html

153B

12. The MNIST example/13.2 TensorFlow MNIST - Complete Code.html

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13. Business case/1. Exploring the dataset and identifying predictors.mp4

78.16MB

13. Business case/1. Exploring the dataset and identifying predictors.vtt

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13. Business case/1.1 Audiobooks_data.csv.csv

625.21KB

13. Business case/2. Outlining the business case solution.mp4

7.95MB

13. Business case/2. Outlining the business case solution.vtt

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13. Business case/3. Balancing the dataset.mp4

35.19MB

13. Business case/3. Balancing the dataset.vtt

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13. Business case/4. Preprocessing the data.mp4

92MB

13. Business case/4. Preprocessing the data.vtt

10.95KB

13. Business case/4.1 TensorFlow Business Case - Preprocessing with Comments.html

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13. Business case/4.2 TensorFlow Business Case - Preprocessing.html

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13. Business case/4.3 Audiobooks_data.csv.csv

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13. Business case/5. Preprocessing exercise.html

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13. Business case/5.1 TensorFlow Business Case - Preprocessing Exercise Solution.html

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13. Business case/5.2 Audiobooks_data.csv.csv

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13. Business case/5.3 TensorFlow Business Case - Preprocessing Exercise.html

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13. Business case/6. Load the preprocessed data.mp4

19.38MB

13. Business case/6. Load the preprocessed data.vtt

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13. Business case/7. Load the preprocessed data - Exercise.html

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13. Business case/7.1 TensorFlow Business Case - Machine Learning - Part 1.html

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13. Business case/8. Learning and interpreting the result.mp4

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13. Business case/8. Learning and interpreting the result.vtt

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13. Business case/8.1 TensorFlow Business Case - Machine Learning - Part 2.html

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13. Business case/9. Setting an early stopping mechanism.mp4

53.36MB

13. Business case/9. Setting an early stopping mechanism.vtt

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13. Business case/9.1 TensorFlow Business Case - Machine Learning - Part 3.html

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13. Business case/10. Setting an early stopping mechanism - Exercise.html

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13. Business case/11. Testing the model.mp4

12.07MB

13. Business case/11. Testing the model.vtt

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13. Business case/11.1 TensorFlow Business Case - Machine Learning Complete Code with Comments.html

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13. Business case/12. Final exercise.html

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13. Business case/12.1 TensorFlow Business Case - Machine Learning Complete Code with Comments.html

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14. Appendix Linear Algebra Fundamentals/1. What is a Matrix.mp4

33.59MB

14. Appendix Linear Algebra Fundamentals/1. What is a Matrix.vtt

3.8KB

14. Appendix Linear Algebra Fundamentals/2. Scalars and Vectors.mp4

33.84MB

14. Appendix Linear Algebra Fundamentals/2. Scalars and Vectors.vtt

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14. Appendix Linear Algebra Fundamentals/3. Linear Algebra and Geometry.mp4

49.79MB

14. Appendix Linear Algebra Fundamentals/3. Linear Algebra and Geometry.vtt

3.54KB

14. Appendix Linear Algebra Fundamentals/4. Scalars, Vectors and Matrices in Python.mp4

26.67MB

14. Appendix Linear Algebra Fundamentals/4. Scalars, Vectors and Matrices in Python.vtt

5.31KB

14. Appendix Linear Algebra Fundamentals/4.1 Scalars, Vectors and Matrices Python Notebook.html

181B

14. Appendix Linear Algebra Fundamentals/5. Tensors.mp4

22.51MB

14. Appendix Linear Algebra Fundamentals/5. Tensors.vtt

3.17KB

14. Appendix Linear Algebra Fundamentals/5.1 Tensors Notebook.html

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14. Appendix Linear Algebra Fundamentals/6. Addition and Subtraction of Matrices.mp4

32.61MB

14. Appendix Linear Algebra Fundamentals/6. Addition and Subtraction of Matrices.vtt

3.48KB

14. Appendix Linear Algebra Fundamentals/6.1 Addition and Subtraction Python Notebook.html

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14. Appendix Linear Algebra Fundamentals/7. Errors when Adding Matrices.mp4

11.17MB

14. Appendix Linear Algebra Fundamentals/7. Errors when Adding Matrices.vtt

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14. Appendix Linear Algebra Fundamentals/7.1 Errors when Adding Matrices Python Notebook.html

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14. Appendix Linear Algebra Fundamentals/8. Transpose of a Matrix.mp4

38.09MB

14. Appendix Linear Algebra Fundamentals/8. Transpose of a Matrix.vtt

4.69KB

14. Appendix Linear Algebra Fundamentals/8.1 Transpose of a Matrix Python Notebook.html

167B

14. Appendix Linear Algebra Fundamentals/9. Dot Product of Vectors.mp4

23.99MB

14. Appendix Linear Algebra Fundamentals/9. Dot Product of Vectors.vtt

3.68KB

14. Appendix Linear Algebra Fundamentals/9.1 Dot Product Python Notebook.html

154B

14. Appendix Linear Algebra Fundamentals/10. Dot Product of Matrices.mp4

49.38MB

14. Appendix Linear Algebra Fundamentals/10. Dot Product of Matrices.vtt

8.22KB

14. Appendix Linear Algebra Fundamentals/10.1 Dot Product of Matrices Python Notebook.html

171B

Udemy Course downloader.txt

94B

14. Appendix Linear Algebra Fundamentals/11. Why is Linear Algebra Useful.vtt

10.31KB

15. Conclusion/1. See how much you have learned.mp4

13.96MB

15. Conclusion/1. See how much you have learned.vtt

4.61KB

15. Conclusion/2. What’s further out there in the machine and deep learning world.mp4

6.26MB

15. Conclusion/2. What’s further out there in the machine and deep learning world.vtt

2.27KB

15. Conclusion/3. An overview of CNNs.mp4

10.93MB

15. Conclusion/3. An overview of CNNs.vtt

5.67KB

15. Conclusion/4. How DeepMind uses deep learning.html

1.36KB

15. Conclusion/5. An overview of RNNs.mp4

4.86MB

15. Conclusion/5. An overview of RNNs.vtt

3.25KB

15. Conclusion/6. An overview of non-NN approaches.mp4

7.85MB

15. Conclusion/6. An overview of non-NN approaches.vtt

4.58KB

16. Bonus lecture/1. Bonus lecture Next steps.html

2.51KB

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