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[DesireCourse.Net] Udemy - Master Deep Learning with TensorFlow in Python

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File Name
Size
1. Welcome! Course introduction/1. Meet your instructors and why you should study machine learning.mp4
106 MB
1. Welcome! Course introduction/1. Meet your instructors and why you should study machine learning.vtt
8.8 kB
1. Welcome! Course introduction/2. What does the course cover.mp4
16 MB
1. Welcome! Course introduction/2. What does the course cover.vtt
5.5 kB
1. Welcome! Course introduction/3. What does the course cover - Quiz.html
161 B
10. Gradient descent and learning rates/1. Stochastic gradient descent.mp4
9.4 MB
10. Gradient descent and learning rates/1. Stochastic gradient descent.vtt
4.2 kB
10. Gradient descent and learning rates/2. Gradient descent pitfalls.mp4
4.3 MB
10. Gradient descent and learning rates/2. Gradient descent pitfalls.vtt
2.5 kB
10. Gradient descent and learning rates/3. Momentum.mp4
6.1 MB
10. Gradient descent and learning rates/3. Momentum.vtt
3.1 kB
10. Gradient descent and learning rates/4. Learning rate schedules.mp4
10 MB
10. Gradient descent and learning rates/4. Learning rate schedules.vtt
5.3 kB
10. Gradient descent and learning rates/5. Learning rate schedules. A picture.mp4
3.1 MB
10. Gradient descent and learning rates/5. Learning rate schedules. A picture.vtt
1.9 kB
10. Gradient descent and learning rates/6. Adaptive learning rate schedules.mp4
8.9 MB
10. Gradient descent and learning rates/6. Adaptive learning rate schedules.vtt
4.6 kB
10. Gradient descent and learning rates/7. Adaptive moment estimation.mp4
7.8 MB
10. Gradient descent and learning rates/7. Adaptive moment estimation.vtt
2.9 kB
11. Preprocessing/1. Preprocessing introduction.mp4
8.4 MB
11. Preprocessing/1. Preprocessing introduction.vtt
3.4 kB
11. Preprocessing/2. Basic preprocessing.mp4
3.7 MB
11. Preprocessing/2. Basic preprocessing.vtt
1.5 kB
11. Preprocessing/3. Standardization.mp4
8.3 MB
11. Preprocessing/3. Standardization.vtt
5.3 kB
11. Preprocessing/4. Dealing with categorical data.mp4
6.1 MB
11. Preprocessing/4. Dealing with categorical data.vtt
2.4 kB
11. Preprocessing/5. One-hot and binary encoding.mp4
6.2 MB
11. Preprocessing/5. One-hot and binary encoding.vtt
4.2 kB
12. The MNIST example/1. The dataset.mp4
7.4 MB
12. The MNIST example/1. The dataset.vtt
3.1 kB
12. The MNIST example/10. MNIST - exercises.html
2.3 kB
12. The MNIST example/10.1 MNIST_Exercises_All.html
144 B
12. The MNIST example/11. MNIST - solutions.html
2.2 kB
12. The MNIST example/11.1 MNIST_Depth_Solution.html
150 B
12. The MNIST example/11.10 MNIST_Learning_rate_Part_1_Solution.html
165 B
12. The MNIST example/11.11 TensorFlow_MNIST_Activation_functions_Part_1_Solution.html
172 B
12. The MNIST example/11.2 MNIST_take_note_of_time_Solution.html
162 B
12. The MNIST example/11.3 Width_and_Depth_Solution.html
160 B
12. The MNIST example/11.4 MNIST_Learning_rate_Part_2_Solution.html
165 B
12. The MNIST example/11.5 MNIST_around_98_percent_accuracy_solution.html
157 B
12. The MNIST example/11.6 MNIST_Batch_size_Part_2_Solution.html
162 B
12. The MNIST example/11.7 MNIST_Width_Solution.html
150 B
12. The MNIST example/11.8 MNIST_Batch_size_Part_1_Solution.html
162 B
12. The MNIST example/11.9 MNIST_Activation_functions_Part_2_Solution.html
172 B
12. The MNIST example/2. How to tackle the MNIST.mp4
7.3 MB
12. The MNIST example/2. How to tackle the MNIST.vtt
3.2 kB
12. The MNIST example/3. Importing the relevant packages.mp4
5.5 MB
12. The MNIST example/3. Importing the relevant packages.vtt
1.9 kB
12. The MNIST example/3.1 TensorFlow_MNIST_with_comments_Part_1.html
159 B
12. The MNIST example/4. Outlining the model.mp4
18 MB
12. The MNIST example/4. Outlining the model.vtt
7.8 kB
12. The MNIST example/4.1 TensorFlow_MNIST_with_comments_Part_2.html
159 B
12. The MNIST example/5. Declaring the loss and the optimization algorithm.mp4
7.1 MB
12. The MNIST example/5. Declaring the loss and the optimization algorithm.vtt
3.1 kB
12. The MNIST example/5.1 TensorFlow_MNIST_with_comments_Part_3.html
159 B
12. The MNIST example/6. Accuracy of prediction.mp4
12 MB
12. The MNIST example/6. Accuracy of prediction.vtt
4.6 kB
12. The MNIST example/6.1 TensorFlow_MNIST_with_comments_Part_4.html
159 B
12. The MNIST example/7. Batching and early stopping.mp4
4.6 MB
12. The MNIST example/7. Batching and early stopping.vtt
2.5 kB
12. The MNIST example/7.1 TensorFlow_MNIST_with_comments_Part_5.html
159 B
12. The MNIST example/8. Learning.mp4
16 MB
12. The MNIST example/8. Learning.vtt
8.9 kB
12. The MNIST example/8.1 TensorFlow_MNIST_with_comments_Part_6.html
159 B
12. The MNIST example/9. Discuss the results and test.mp4
22 MB
12. The MNIST example/9. Discuss the results and test.vtt
7.2 kB
12. The MNIST example/9.1 TensorFlow_MNIST_with_comments.html
152 B
13. Business case/1. Exploring the dataset and identifying predictors.mp4
23 MB
13. Business case/1. Exploring the dataset and identifying predictors.vtt
9.4 kB
13. Business case/1.1 Audiobooks_data.csv.csv
711 kB
13. Business case/10. Testing the model.mp4
4.3 MB
13. Business case/10. Testing the model.vtt
2.3 kB
13. Business case/11. A comment on the homework.mp4
13 MB
13. Business case/11. A comment on the homework.vtt
4.6 kB
13. Business case/11.1 Homework exercise.html
134 B
13. Business case/12. Final exercise.html
441 B
13. Business case/12.1 Homework exercise.html
134 B
13. Business case/2. Outlining the business case solution.mp4
3.8 MB
13. Business case/2. Outlining the business case solution.vtt
2.2 kB
13. Business case/3. Balancing the dataset.mp4
14 MB
13. Business case/3. Balancing the dataset.vtt
3.9 kB
13. Business case/4. Preprocessing the data.mp4
34 MB
13. Business case/4. Preprocessing the data.vtt
12 kB
13. Business case/4.1 Preprocessing.html
134 B
13. Business case/5. Preprocessing exercise.html
394 B
13. Business case/5.1 Preprocessing exercise.html
134 B
13. Business case/6. Create a class for batching.mp4
28 MB
13. Business case/6. Create a class for batching.vtt
6.9 kB
13. Business case/6.1 Class.html
134 B
13. Business case/7. Outlining the model.mp4
20 MB
13. Business case/7. Outlining the model.vtt
6.1 kB
13. Business case/7.1 Outlining the model.html
134 B
13. Business case/8. Optimizing the algorithm.mp4
12 MB
13. Business case/8. Optimizing the algorithm.vtt
5.7 kB
13. Business case/8.1 Optimizing the algorithm.html
134 B
13. Business case/9. Interpreting the result.mp4
5.4 MB
13. Business case/9. Interpreting the result.vtt
2.6 kB
13. Business case/9.1 Interpreting the result.html
134 B
14. Appendix Linear Algebra Fundamentals/1. What is a Matrix.mp4
34 MB
14. Appendix Linear Algebra Fundamentals/1. What is a Matrix.vtt
3.8 kB
14. Appendix Linear Algebra Fundamentals/10. Dot Product of Matrices.mp4
49 MB
14. Appendix Linear Algebra Fundamentals/10. Dot Product of Matrices.vtt
8.2 kB
14. Appendix Linear Algebra Fundamentals/10.1 Dot Product of Matrices Python Notebook.html
171 B
14. Appendix Linear Algebra Fundamentals/11. Why is Linear Algebra Useful.mp4
144 MB
14. Appendix Linear Algebra Fundamentals/11. Why is Linear Algebra Useful.vtt
10 kB
14. Appendix Linear Algebra Fundamentals/2. Scalars and Vectors.mp4
34 MB
14. Appendix Linear Algebra Fundamentals/2. Scalars and Vectors.vtt
3.3 kB
14. Appendix Linear Algebra Fundamentals/3. Linear Algebra and Geometry.mp4
50 MB
14. Appendix Linear Algebra Fundamentals/3. Linear Algebra and Geometry.vtt
3.5 kB
14. Appendix Linear Algebra Fundamentals/4. Scalars, Vectors and Matrices in Python.mp4
27 MB
14. Appendix Linear Algebra Fundamentals/4. Scalars, Vectors and Matrices in Python.vtt
5.3 kB
14. Appendix Linear Algebra Fundamentals/4.1 Scalars, Vectors and Matrices Python Notebook.html
181 B
14. Appendix Linear Algebra Fundamentals/5. Tensors.mp4
22 MB
14. Appendix Linear Algebra Fundamentals/5. Tensors.vtt
3.2 kB
14. Appendix Linear Algebra Fundamentals/5.1 Tensors Notebook.html
148 B
14. Appendix Linear Algebra Fundamentals/6. Addition and Subtraction of Matrices.mp4
33 MB
14. Appendix Linear Algebra Fundamentals/6. Addition and Subtraction of Matrices.vtt
3.5 kB
14. Appendix Linear Algebra Fundamentals/6.1 Addition and Subtraction Python Notebook.html
178 B
14. Appendix Linear Algebra Fundamentals/7. Errors when Adding Matrices.mp4
11 MB
14. Appendix Linear Algebra Fundamentals/7. Errors when Adding Matrices.vtt
2.3 kB
14. Appendix Linear Algebra Fundamentals/7.1 Errors when Adding Matrices Python Notebook.html
220 B
14. Appendix Linear Algebra Fundamentals/8. Transpose of a Matrix.mp4
38 MB
14. Appendix Linear Algebra Fundamentals/8. Transpose of a Matrix.vtt
4.7 kB
14. Appendix Linear Algebra Fundamentals/8.1 Transpose of a Matrix Python Notebook.html
167 B
14. Appendix Linear Algebra Fundamentals/9. Dot Product of Vectors.mp4
24 MB
14. Appendix Linear Algebra Fundamentals/9. Dot Product of Vectors.vtt
3.7 kB
14. Appendix Linear Algebra Fundamentals/9.1 Dot Product Python Notebook.html
154 B
15. Conclusion/1. See how much you have learned.mp4
14 MB
15. Conclusion/1. See how much you have learned.vtt
4.6 kB
15. Conclusion/2. What’s further out there in the machine and deep learning world.mp4
6.3 MB
15. Conclusion/2. What’s further out there in the machine and deep learning world.vtt
2.3 kB
15. Conclusion/3. An overview of CNNs.mp4
11 MB
15. Conclusion/3. An overview of CNNs.vtt
5.7 kB
15. Conclusion/4. How DeepMind uses deep learning.html
1.4 kB
15. Conclusion/5. An overview of RNNs.mp4
4.9 MB
15. Conclusion/5. An overview of RNNs.vtt
3.2 kB
15. Conclusion/6. An overview of non-NN approaches.mp4
7.8 MB
15. Conclusion/6. An overview of non-NN approaches.vtt
4.6 kB
16. Bonus lecture/1. Bonus lecture Next steps.html
2.5 kB
2. Introduction to neural networks/1. Introduction to neural networks.mp4
14 MB
2. Introduction to neural networks/1. Introduction to neural networks.vtt
5.2 kB
2. Introduction to neural networks/1.1 Course Notes - Section 2.pdf.pdf
928 kB
2. Introduction to neural networks/10. The linear model. Multiple inputs.mp4
7.5 MB
2. Introduction to neural networks/10. The linear model. Multiple inputs.vtt
2.7 kB
2. Introduction to neural networks/10.1 Course Notes - Section 2.pdf.pdf
928 kB
2. Introduction to neural networks/11. The linear model. Multiple inputs - Quiz.html
161 B
2. Introduction to neural networks/12. The linear model. Multiple inputs and multiple outputs.mp4
38 MB
2. Introduction to neural networks/12. The linear model. Multiple inputs and multiple outputs.vtt
4.8 kB
2. Introduction to neural networks/12.1 Course Notes - Section 2.pdf.pdf
928 kB
2. Introduction to neural networks/13. The linear model. Multiple inputs and multiple outputs - Quiz.html
161 B
2. Introduction to neural networks/14. Graphical representation.mp4
6.4 MB
2. Introduction to neural networks/14. Graphical representation.vtt
2.3 kB
2. Introduction to neural networks/14.1 Course Notes - Section 2.pdf.pdf
928 kB
2. Introduction to neural networks/15. Graphical representation - Quiz.html
161 B
2. Introduction to neural networks/16. The objective function.mp4
5.7 MB
2. Introduction to neural networks/16. The objective function.vtt
1.8 kB
2. Introduction to neural networks/16.1 Course Notes - Section 2.pdf.pdf
928 kB
2. Introduction to neural networks/17. The objective function - Quiz.html
161 B
2. Introduction to neural networks/18. L2-norm loss.mp4
7.3 MB
2. Introduction to neural networks/18. L2-norm loss.vtt
2.5 kB
2. Introduction to neural networks/18.1 Course Notes - Section 2.pdf.pdf
928 kB
2. Introduction to neural networks/19. L2-norm loss - Quiz.html
161 B
2. Introduction to neural networks/2. Introduction to neural networks - Quiz.html
161 B
2. Introduction to neural networks/20. Cross-entropy loss.mp4
11 MB
2. Introduction to neural networks/20. Cross-entropy loss.vtt
4.6 kB
2. Introduction to neural networks/20.1 Course Notes - Section 2.pdf.pdf
928 kB
2. Introduction to neural networks/21. Cross-entropy loss - Quiz.html
161 B
2. Introduction to neural networks/22. One parameter gradient descent.mp4
18 MB
2. Introduction to neural networks/22. One parameter gradient descent.vtt
7.4 kB
2. Introduction to neural networks/22.1 GD-function-example.xlsx.xlsx
42 kB
2. Introduction to neural networks/22.2 Course Notes - Section 2.pdf.pdf
928 kB
2. Introduction to neural networks/23. One parameter gradient descent - Quiz.html
161 B
2. Introduction to neural networks/24. N-parameter gradient descent.mp4
40 MB
2. Introduction to neural networks/24. N-parameter gradient descent.vtt
6.6 kB
2. Introduction to neural networks/24.1 Course Notes - Section 2.pdf.pdf
928 kB
2. Introduction to neural networks/25. N-parameter gradient descent - Quiz.html
161 B
2. Introduction to neural networks/3. Training the model.mp4
8.8 MB
2. Introduction to neural networks/3. Training the model.vtt
3.8 kB
2. Introduction to neural networks/3.1 Course Notes - Section 2.pdf.pdf
928 kB
2. Introduction to neural networks/4. Training the model - Quiz.html
161 B
2. Introduction to neural networks/5. Types of machine learning.mp4
12 MB
2. Introduction to neural networks/5. Types of machine learning.vtt
4.6 kB
2. Introduction to neural networks/5.1 Course Notes - Section 2.pdf.pdf
928 kB
2. Introduction to neural networks/6. Types of machine learning - Quiz.html
161 B
2. Introduction to neural networks/7. The linear model.mp4
9.1 MB
2. Introduction to neural networks/7. The linear model.vtt
3.5 kB
2. Introduction to neural networks/7.1 Course Notes - Section 2.pdf.pdf
928 kB
2. Introduction to neural networks/8. The linear model - Quiz.html
161 B
2. Introduction to neural networks/9. Need Help with Linear Algebra.html
829 B
3. Setting up the working environment/1. Setting up the environment - An introduction - Do not skip, please!.mp4
2.6 MB
3. Setting up the working environment/1. Setting up the environment - An introduction - Do not skip, please!.vtt
1.1 kB
3. Setting up the working environment/10. Installing packages - exercise.html
227 B
3. Setting up the working environment/11. Installing packages - solution.html
339 B
3. Setting up the working environment/2. Why Python and why Jupyter.mp4
14 MB
3. Setting up the working environment/2. Why Python and why Jupyter.vtt
5.6 kB
3. Setting up the working environment/3. Why Python and why Jupyter - Quiz.html
161 B
3. Setting up the working environment/4. Installing Anaconda.mp4
9.4 MB
3. Setting up the working environment/4. Installing Anaconda.vtt
4.1 kB
3. Setting up the working environment/5. The Jupyter dashboard - part 1.mp4
5.6 MB
3. Setting up the working environment/5. The Jupyter dashboard - part 1.vtt
2.8 kB
3. Setting up the working environment/6. The Jupyter dashboard - part 2.mp4
11 MB
3. Setting up the working environment/6. The Jupyter dashboard - part 2.vtt
6.0 kB
3. Setting up the working environment/7. Jupyter Shortcuts.html
332 B
3. Setting up the working environment/7.1 Shortcuts for Jupyter.pdf.pdf
619 kB
3. Setting up the working environment/8. The Jupyter dashboard - Quiz.html
161 B
3. Setting up the working environment/9. Installing the TensorFlow package.mp4
4.9 MB
3. Setting up the working environment/9. Installing the TensorFlow package.vtt
2.8 kB
4. Minimal example - your first machine learning algorithm/1. Minimal example - part 1.mp4
6.5 MB
4. Minimal example - your first machine learning algorithm/1. Minimal example - part 1.vtt
3.9 kB
4. Minimal example - your first machine learning algorithm/1.1 Minimal example Part 1.html
136 B
4. Minimal example - your first machine learning algorithm/2. Minimal example - part 2.mp4
11 MB
4. Minimal example - your first machine learning algorithm/2. Minimal example - part 2.vtt
5.9 kB
4. Minimal example - your first machine learning algorithm/2.1 Minimal example - part 2.html
136 B
4. Minimal example - your first machine learning algorithm/3. Minimal example - part 3.mp4
9.8 MB
4. Minimal example - your first machine learning algorithm/3. Minimal example - part 3.vtt
3.9 kB
4. Minimal example - your first machine learning algorithm/3.1 Minimal example - part 3.html
136 B
4. Minimal example - your first machine learning algorithm/4. Minimal example - part 4.mp4
21 MB
4. Minimal example - your first machine learning algorithm/4. Minimal example - part 4.vtt
9.5 kB
4. Minimal example - your first machine learning algorithm/4.1 Minimal example - part 4.html
145 B
4. Minimal example - your first machine learning algorithm/5. Minimal example - Exercises.html
1.6 kB
4. Minimal example - your first machine learning algorithm/5.1 Minimal_example_Exercise_2_Solution.html
149 B
4. Minimal example - your first machine learning algorithm/5.10 Minimal_example_Exercise_6_Solution.html
149 B
4. Minimal example - your first machine learning algorithm/5.2 Minimal_example_Exercise_3.d. Solution.html
154 B
4. Minimal example - your first machine learning algorithm/5.3 Minimal_example_Exercise_4_Solution.html
149 B
4. Minimal example - your first machine learning algorithm/5.4 Minimal_example_Exercise_3.b. Solution.html
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4. Minimal example - your first machine learning algorithm/5.5 Minimal_example_All_Exercises.html
143 B
4. Minimal example - your first machine learning algorithm/5.6 Minimal_example_Exercise_1_Solution.html
149 B
4. Minimal example - your first machine learning algorithm/5.7 Minimal_example_Exercise_3.c. Solution.html
154 B
4. Minimal example - your first machine learning algorithm/5.8 Minimal_example_Exercise_5_Solution.html
149 B
4. Minimal example - your first machine learning algorithm/5.9 Minimal_example_Exercise_3.a. Solution.html
154 B
5. TensorFlow - An introduction/1. TensorFlow outline.mp4
14 MB
5. TensorFlow - An introduction/1. TensorFlow outline.vtt
4.6 kB
5. TensorFlow - An introduction/2. TensorFlow intro.mp4
7.5 MB
5. TensorFlow - An introduction/2. TensorFlow intro.vtt
1.9 kB
5. TensorFlow - An introduction/3. Types of file formats in TensorFlow.mp4
5.8 MB
5. TensorFlow - An introduction/3. Types of file formats in TensorFlow.vtt
3.0 kB
5. TensorFlow - An introduction/3.1 TensorFlow Minimal example - Part 1.html
154 B
5. TensorFlow - An introduction/4. Inputs, outputs, targets, weights, biases - model layout.mp4
13 MB
5. TensorFlow - An introduction/4. Inputs, outputs, targets, weights, biases - model layout.vtt
6.4 kB
5. TensorFlow - An introduction/4.1 TensorFlow Minimal example - Part 2.html
154 B
5. TensorFlow - An introduction/5. Loss function and gradient descent - introducing optimizers.mp4
9.7 MB
5. TensorFlow - An introduction/5. Loss function and gradient descent - introducing optimizers.vtt
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5. TensorFlow - An introduction/5.1 TensorFlow Minimal example - Part 3.html
154 B
5. TensorFlow - An introduction/6. Model output.mp4
14 MB
5. TensorFlow - An introduction/6. Model output.vtt
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5. TensorFlow - An introduction/6.1 TensorFlow - Minimal example complete.html
156 B
5. TensorFlow - An introduction/7. Minimal example - Exercises.html
1.6 kB
5. TensorFlow - An introduction/7.1 TensorFlow_Minimal_Example_Exercise_1_Solution.html
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5. TensorFlow - An introduction/7.2 TensorFlow_Minimal_Example_Exercise_2_3_Solution.html
162 B
5. TensorFlow - An introduction/7.3 TensorFlow_Minimal_Example_Exercise_2_1_Solution.html
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5. TensorFlow - An introduction/7.4 TensorFlow_Minimal_Example_All_Exercises.html
154 B
5. TensorFlow - An introduction/7.5 TensorFlow_Minimal_Example_Exercise_3_Solution.html
160 B
5. TensorFlow - An introduction/7.6 TensorFlow_Minimal_Example_Exercise_2_2_Solution.html
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5. TensorFlow - An introduction/7.7 TensorFlow_Minimal_Example_Exercise_4_Solution.html
160 B
5. TensorFlow - An introduction/7.8 TensorFlow_Minimal_Example_Exercise_2_4_Solution.html
162 B
6. Going deeper Introduction to deep neural networks/1. Layers.mp4
4.7 MB
6. Going deeper Introduction to deep neural networks/1. Layers.vtt
2.2 kB
6. Going deeper Introduction to deep neural networks/1.1 Course Notes - Section 6.pdf.pdf
936 kB
6. Going deeper Introduction to deep neural networks/2. What is a deep net.mp4
6.7 MB
6. Going deeper Introduction to deep neural networks/2. What is a deep net.vtt
2.9 kB
6. Going deeper Introduction to deep neural networks/2.1 Course Notes - Section 6.pdf.pdf
936 kB
6. Going deeper Introduction to deep neural networks/3. Understanding deep nets in depth.mp4
13 MB
6. Going deeper Introduction to deep neural networks/3. Understanding deep nets in depth.vtt
5.8 kB
6. Going deeper Introduction to deep neural networks/4. Why do we need non-linearities.mp4
9.0 MB
6. Going deeper Introduction to deep neural networks/4. Why do we need non-linearities.vtt
3.3 kB
6. Going deeper Introduction to deep neural networks/5. Activation functions.mp4
8.7 MB
6. Going deeper Introduction to deep neural networks/5. Activation functions.vtt
4.5 kB
6. Going deeper Introduction to deep neural networks/6. Softmax activation.mp4
7.4 MB
6. Going deeper Introduction to deep neural networks/6. Softmax activation.vtt
7.4 MB
6. Going deeper Introduction to deep neural networks/7. Backpropagation.mp4
11 MB
6. Going deeper Introduction to deep neural networks/7. Backpropagation.vtt
6.5 MB
6. Going deeper Introduction to deep neural networks/8. Backpropagation - visual representation.mp4
6.8 MB
6. Going deeper Introduction to deep neural networks/8. Backpropagation - visual representation.vtt
3.5 kB
7. Backpropagation. A peek into the Mathematics of Optimization/1. Backpropagation. A peek into the Mathematics of Optimization.html
539 B
7. Backpropagation. A peek into the Mathematics of Optimization/1.1 Backpropagation-a-peek-into-the-Mathematics-of-Optimization.pdf.pdf
182 kB
8. Overfitting/1. Underfitting and overfitting.mp4
11 MB
8. Overfitting/1. Underfitting and overfitting.vtt
5.0 kB
8. Overfitting/2. Underfitting and overfitting - classification.mp4
6.8 MB
8. Overfitting/2. Underfitting and overfitting - classification.vtt
2.4 kB
8. Overfitting/3. Training and validation.mp4
9.2 MB
8. Overfitting/3. Training and validation.vtt
4.2 kB
8. Overfitting/4. Training, validation, and test.mp4
7.4 MB
8. Overfitting/4. Training, validation, and test.vtt
3.1 kB
8. Overfitting/5. N-fold cross validation.mp4
7.0 MB
8. Overfitting/5. N-fold cross validation.vtt
3.7 kB
8. Overfitting/6. Early stopping.mp4
9.4 MB
8. Overfitting/6. Early stopping.vtt
6.0 kB
9. Initialization/1. Initialization - Introduction.mp4
8.0 MB
9. Initialization/1. Initialization - Introduction.vtt
3.1 kB
9. Initialization/2. Types of simple initializations.mp4
5.6 MB
9. Initialization/2. Types of simple initializations.vtt
3.2 kB
9. Initialization/3. Xavier initialization.mp4
5.8 MB
9. Initialization/3. Xavier initialization.vtt
3.2 kB
[CourseClub.Me].url
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[DesireCourse.Net].url
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