TorBT - Torrents and Magnet Links Search Engine
Latest Searches: il decamerone proibito, thc, boobs/, 小6, dastardly & muttley in their flying machines, 网盘, cds%2f, iqqq-025, atid-491/, school+models

[DesireCourse.Net] Udemy - Deep Learning with TensorFlow 2.0 [2020]

Magnet Download Download Torrent
File Name
Size
0. Websites you may like/[CourseClub.Me].url
48 B
0. Websites you may like/[DesireCourse.Net].url
51 B
0. Websites you may like/[FreeCourseWorld.Com].url
54 B
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.srt
10 kB
1. Welcome! Course introduction/2. What does the course cover.mp4
16 MB
1. Welcome! Course introduction/2. What does the course cover.srt
6.2 kB
1. Welcome! Course introduction/3. What does the course cover - Quiz.html
168 B
1. Welcome! Course introduction/4. Download All Resources and Important FAQ.html
720 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.srt
4.9 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.srt
2.8 kB
10. Gradient descent and learning rates/3. Momentum.mp4
6.1 MB
10. Gradient descent and learning rates/3. Momentum.srt
3.5 kB
10. Gradient descent and learning rates/4. Learning rate schedules.mp4
10 MB
10. Gradient descent and learning rates/4. Learning rate schedules.srt
6.0 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.srt
2.2 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.srt
5.2 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.srt
3.3 kB
11. Preprocessing/1. Preprocessing introduction.mp4
8.4 MB
11. Preprocessing/1. Preprocessing introduction.srt
3.9 kB
11. Preprocessing/2. Basic preprocessing.mp4
3.7 MB
11. Preprocessing/2. Basic preprocessing.srt
1.7 kB
11. Preprocessing/3. Standardization.mp4
8.3 MB
11. Preprocessing/3. Standardization.srt
6.0 kB
11. Preprocessing/4. Dealing with categorical data.mp4
6.1 MB
11. Preprocessing/4. Dealing with categorical data.srt
2.8 kB
11. Preprocessing/5. One-hot and binary encoding.mp4
6.2 MB
11. Preprocessing/5. One-hot and binary encoding.srt
4.8 kB
12. The MNIST example/1. The dataset.mp4
13 MB
12. The MNIST example/1. The dataset.srt
3.6 kB
12. The MNIST example/10. Learning.mp4
41 MB
12. The MNIST example/10. Learning.srt
7.9 kB
12. The MNIST example/10.1 TensorFlow MNIST - Part 6 with comments.html
150 B
12. The MNIST example/11. MNIST - exercises.html
2.0 kB
12. The MNIST example/11.1 TensorFlow MNIST - All Exercises.html
144 B
12. The MNIST example/12. MNIST - solutions.html
2.1 kB
12. The MNIST example/12.1 8. TensorFlow MNIST - Exercise 8 Solution.html
165 B
12. The MNIST example/12.10 10. TensorFlow MNIST - Exercise 10 Solution.html
157 B
12. The MNIST example/12.2 1. TensorFlow MNIST - Exercise 1 Solution.html
150 B
12. The MNIST example/12.3 5. TensorFlow MNIST - Exercise 5 Solution.html
172 B
12. The MNIST example/12.4 9. TensorFlow MNIST - Exercise 9 Solution.html
165 B
12. The MNIST example/12.5 6. TensorFlow MNIST - Exercise 6 Solution.html
162 B
12. The MNIST example/12.6 7. TensorFlow MNIST - Exercise 7 Solution.html
162 B
12. The MNIST example/12.7 3. TensorFlow MNIST - Exercise 3 Solution.html
160 B
12. The MNIST example/12.8 4. TensorFlow MNIST - Exercise 4 Solution.html
172 B
12. The MNIST example/12.9 2. TensorFlow MNIST - Exercise 2 Solution.html
150 B
12. The MNIST example/13. Testing the model.mp4
30 MB
12. The MNIST example/13. Testing the model.srt
6.0 kB
12. The MNIST example/13.1 TensorFlow MNIST - Complete Code with Comments.html
153 B
12. The MNIST example/13.2 TensorFlow MNIST - Complete Code.html
139 B
12. The MNIST example/2. How to tackle the MNIST.mp4
19 MB
12. The MNIST example/2. How to tackle the MNIST.srt
3.5 kB
12. The MNIST example/3. Importing the relevant packages and load the data.mp4
16 MB
12. The MNIST example/3. Importing the relevant packages and load the data.srt
3.1 kB
12. The MNIST example/3.1 TensorFlow MNIST - Part 1 with comments.html
150 B
12. The MNIST example/4. Preprocess the data - create a validation dataset and scale the data.mp4
29 MB
12. The MNIST example/4. Preprocess the data - create a validation dataset and scale the data.srt
6.3 kB
12. The MNIST example/5. Preprocess the data - scale the test data.html
81 B
12. The MNIST example/5.1 TensorFlow MNIST - Part 2 with comments.html
150 B
12. The MNIST example/6. Preprocess the data - shuffle and batch the data.mp4
42 MB
12. The MNIST example/6. Preprocess the data - shuffle and batch the data.srt
9.3 kB
12. The MNIST example/7. Preprocess the data - shuffle and batch the data.html
81 B
12. The MNIST example/7.1 TensorFlow MNIST - Part 3 with comments.html
150 B
12. The MNIST example/8. Outline the model.mp4
28 MB
12. The MNIST example/8. Outline the model.srt
7.2 kB
12. The MNIST example/8.1 TensorFlow MNIST - Part 4 with comments.html
150 B
12. The MNIST example/9. Select the loss and the optimizer.mp4
14 MB
12. The MNIST example/9. Select the loss and the optimizer.srt
3.0 kB
12. The MNIST example/9.1 TensorFlow MNIST - Part 5 with comments.html
150 B
13. Business case/1. Exploring the dataset and identifying predictors.mp4
66 MB
13. Business case/1. Exploring the dataset and identifying predictors.srt
11 kB
13. Business case/1.1 Audiobooks_data.csv
625 kB
13. Business case/10. Setting an early stopping mechanism - Exercise.html
191 B
13. Business case/11. Testing the model.mp4
11 MB
13. Business case/11. Testing the model.srt
2.0 kB
13. Business case/11.1 TensorFlow Business Case - Machine Learning Complete Code with Comments.html
166 B
13. Business case/12. Final exercise.html
445 B
13. Business case/12.1 TensorFlow Business Case - Machine Learning Complete Code with Comments.html
166 B
13. Business case/2. Outlining the business case solution.mp4
7.3 MB
13. Business case/2. Outlining the business case solution.srt
2.0 kB
13. Business case/3. Balancing the dataset.mp4
30 MB
13. Business case/3. Balancing the dataset.srt
4.5 kB
13. Business case/4. Preprocessing the data.mp4
84 MB
13. Business case/4. Preprocessing the data.srt
12 kB
13. Business case/4.1 Audiobooks_data.csv
625 kB
13. Business case/4.2 TensorFlow Business Case - Preprocessing with Comments.html
163 B
13. Business case/4.3 TensorFlow Business Case - Preprocessing.html
149 B
13. Business case/5. Preprocessing exercise.html
404 B
13. Business case/5.1 TensorFlow Business Case - Preprocessing Exercise.html
158 B
13. Business case/5.2 Audiobooks_data.csv
625 kB
13. Business case/5.3 TensorFlow Business Case - Preprocessing Exercise Solution.html
167 B
13. Business case/6. Load the preprocessed data.mp4
18 MB
13. Business case/6. Load the preprocessed data.srt
4.7 kB
13. Business case/7. Load the preprocessed data - Exercise.html
79 B
13. Business case/7.1 TensorFlow Business Case - Machine Learning - Part 1.html
172 B
13. Business case/8. Learning and interpreting the result.mp4
31 MB
13. Business case/8. Learning and interpreting the result.srt
6.3 kB
13. Business case/8.1 TensorFlow Business Case - Machine Learning - Part 2.html
172 B
13. Business case/9. Setting an early stopping mechanism.mp4
50 MB
13. Business case/9. Setting an early stopping mechanism.srt
7.8 kB
13. Business case/9.1 TensorFlow Business Case - Machine Learning - Part 3.html
172 B
14. Appendix Linear Algebra Fundamentals/1. What is a Matrix.mp4
34 MB
14. Appendix Linear Algebra Fundamentals/1. What is a Matrix.srt
4.3 kB
14. Appendix Linear Algebra Fundamentals/10. Dot Product of Matrices.mp4
49 MB
14. Appendix Linear Algebra Fundamentals/10. Dot Product of Matrices.srt
9.5 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.srt
12 kB
14. Appendix Linear Algebra Fundamentals/2. Scalars and Vectors.mp4
34 MB
14. Appendix Linear Algebra Fundamentals/2. Scalars and Vectors.srt
3.8 kB
14. Appendix Linear Algebra Fundamentals/3. Linear Algebra and Geometry.mp4
50 MB
14. Appendix Linear Algebra Fundamentals/3. Linear Algebra and Geometry.srt
4.1 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.srt
6.1 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.srt
3.6 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.srt
4.0 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.srt
2.6 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.srt
5.4 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.srt
4.3 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.srt
5.2 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.srt
2.5 kB
15. Conclusion/3. An overview of CNNs.mp4
11 MB
15. Conclusion/3. An overview of CNNs.srt
6.5 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.srt
3.6 kB
15. Conclusion/6. An overview of non-NN approaches.mp4
7.8 MB
15. Conclusion/6. An overview of non-NN approaches.srt
5.2 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.srt
5.9 kB
2. Introduction to neural networks/1.1 Course Notes - Section 2.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.srt
3.1 kB
2. Introduction to neural networks/10.1 Course Notes - Section 2.pdf
928 kB
2. Introduction to neural networks/11. The linear model. Multiple inputs - Quiz.html
168 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.srt
5.5 kB
2. Introduction to neural networks/12.1 Course Notes - Section 2.pdf
928 kB
2. Introduction to neural networks/13. The linear model. Multiple inputs and multiple outputs - Quiz.html
168 B
2. Introduction to neural networks/14. Graphical representation.mp4
6.4 MB
2. Introduction to neural networks/14. Graphical representation.srt
2.7 kB
2. Introduction to neural networks/14.1 Course Notes - Section 2.pdf
928 kB
2. Introduction to neural networks/15. Graphical representation - Quiz.html
168 B
2. Introduction to neural networks/16. The objective function.mp4
5.7 MB
2. Introduction to neural networks/16. The objective function.srt
2.0 kB
2. Introduction to neural networks/16.1 Course Notes - Section 2.pdf
928 kB
2. Introduction to neural networks/17. The objective function - Quiz.html
168 B
2. Introduction to neural networks/18. L2-norm loss.mp4
7.3 MB
2. Introduction to neural networks/18. L2-norm loss.srt
2.8 kB
2. Introduction to neural networks/18.1 Course Notes - Section 2.pdf
928 kB
2. Introduction to neural networks/19. L2-norm loss - Quiz.html
168 B
2. Introduction to neural networks/2. Introduction to neural networks - Quiz.html
168 B
2. Introduction to neural networks/20. Cross-entropy loss.mp4
11 MB
2. Introduction to neural networks/20. Cross-entropy loss.srt
5.3 kB
2. Introduction to neural networks/20.1 Course Notes - Section 2.pdf
928 kB
2. Introduction to neural networks/21. Cross-entropy loss - Quiz.html
168 B
2. Introduction to neural networks/22. One parameter gradient descent.mp4
18 MB
2. Introduction to neural networks/22. One parameter gradient descent.srt
8.5 kB
2. Introduction to neural networks/22.1 Course Notes - Section 2.pdf
928 kB
2. Introduction to neural networks/22.2 GD-function-example.xlsx
42 kB
2. Introduction to neural networks/23. One parameter gradient descent - Quiz.html
168 B
2. Introduction to neural networks/24. N-parameter gradient descent.mp4
39 MB
2. Introduction to neural networks/24. N-parameter gradient descent.srt
7.5 kB
2. Introduction to neural networks/24.1 Course Notes - Section 2.pdf
928 kB
2. Introduction to neural networks/25. N-parameter gradient descent - Quiz.html
168 B
2. Introduction to neural networks/3. Training the model.mp4
8.8 MB
2. Introduction to neural networks/3. Training the model.srt
4.3 kB
2. Introduction to neural networks/3.1 Course Notes - Section 2.pdf
928 kB
2. Introduction to neural networks/4. Training the model - Quiz.html
168 B
2. Introduction to neural networks/5. Types of machine learning.mp4
12 MB
2. Introduction to neural networks/5. Types of machine learning.srt
5.3 kB
2. Introduction to neural networks/5.1 Course Notes - Section 2.pdf
928 kB
2. Introduction to neural networks/6. Types of machine learning - Quiz.html
168 B
2. Introduction to neural networks/7. The linear model.mp4
9.1 MB
2. Introduction to neural networks/7. The linear model.srt
3.9 kB
2. Introduction to neural networks/7.1 Course Notes - Section 2.pdf
928 kB
2. Introduction to neural networks/8. The linear model - Quiz.html
168 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
6.0 MB
3. Setting up the working environment/1. Setting up the environment - An introduction - Do not skip, please!.srt
1.4 kB
3. Setting up the working environment/10. Installing packages - exercise.html
198 B
3. Setting up the working environment/11. Installing packages - solution.html
267 B
3. Setting up the working environment/2. Why Python and why Jupyter.mp4
32 MB
3. Setting up the working environment/2. Why Python and why Jupyter.srt
6.3 kB
3. Setting up the working environment/3. Why Python and why Jupyter - Quiz.html
168 B
3. Setting up the working environment/4. Installing Anaconda.mp4
28 MB
3. Setting up the working environment/4. Installing Anaconda.srt
4.6 kB
3. Setting up the working environment/5. The Jupyter dashboard - part 1.mp4
8.7 MB
3. Setting up the working environment/5. The Jupyter dashboard - part 1.srt
3.1 kB
3. Setting up the working environment/6. The Jupyter dashboard - part 2.mp4
19 MB
3. Setting up the working environment/6. The Jupyter dashboard - part 2.srt
6.8 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
619 kB
3. Setting up the working environment/8. The Jupyter dashboard - Quiz.html
168 B
3. Setting up the working environment/9. Installing TensorFlow 2.mp4
39 MB
3. Setting up the working environment/9. Installing TensorFlow 2.srt
6.4 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.srt
4.5 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.srt
6.8 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.srt
4.4 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.srt
11 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_3.b. Solution.html
154 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_5_Solution.html
149 B
4. Minimal example - your first machine learning algorithm/5.3 Minimal_example_Exercise_1_Solution.html
149 B
4. Minimal example - your first machine learning algorithm/5.4 Minimal_example_Exercise_4_Solution.html
149 B
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_3.d. Solution.html
154 B
4. Minimal example - your first machine learning algorithm/5.7 Minimal_example_Exercise_3.a. Solution.html
154 B
4. Minimal example - your first machine learning algorithm/5.8 Minimal_example_Exercise_2_Solution.html
149 B
4. Minimal example - your first machine learning algorithm/5.9 Minimal_example_Exercise_3.c. Solution.html
154 B
5. TensorFlow - An introduction/1. TensorFlow outline.mp4
34 MB
5. TensorFlow - An introduction/1. TensorFlow outline.srt
5.2 kB
5. TensorFlow - An introduction/2. TensorFlow 2 intro.mp4
22 MB
5. TensorFlow - An introduction/2. TensorFlow 2 intro.srt
3.6 kB
5. TensorFlow - An introduction/3. A Note on Coding in TensorFlow.mp4
6.8 MB
5. TensorFlow - An introduction/3. A Note on Coding in TensorFlow.srt
1.4 kB
5. TensorFlow - An introduction/4. Types of file formats in TensorFlow and data handling.mp4
16 MB
5. TensorFlow - An introduction/4. Types of file formats in TensorFlow and data handling.srt
3.5 kB
5. TensorFlow - An introduction/4.1 TensorFlow Minimal Example - Part 1.html
146 B
5. TensorFlow - An introduction/5. Model layout - inputs, outputs, targets, weights, biases, optimizer and loss.mp4
35 MB
5. TensorFlow - An introduction/5. Model layout - inputs, outputs, targets, weights, biases, optimizer and loss.srt
7.8 kB
5. TensorFlow - An introduction/5.1 TensorFlow Minimal Example - Part 2.html
146 B
5. TensorFlow - An introduction/6. Interpreting the result and extracting the weights and bias.mp4
30 MB
5. TensorFlow - An introduction/6. Interpreting the result and extracting the weights and bias.srt
6.2 kB
5. TensorFlow - An introduction/6.1 TensorFlow Minimal Example - Part 3.html
146 B
5. TensorFlow - An introduction/7. Cutomizing your model.mp4
23 MB
5. TensorFlow - An introduction/7. Cutomizing your model.srt
4.1 kB
5. TensorFlow - An introduction/7.1 TensorFlow Minimal Example - Complete Code.html
149 B
5. TensorFlow - An introduction/7.2 TensorFlow Minimal Example - Complete Code with Comments.html
163 B
5. TensorFlow - An introduction/8. Minimal example with TensorFlow - Exercises.html
1.4 kB
5. TensorFlow - An introduction/8.1 TensorFlow Minimal Example - Exercise 1 - Solution.html
160 B
5. TensorFlow - An introduction/8.2 TensorFlow Minimal Example - Exercise 2_1 - Solution.html
162 B
5. TensorFlow - An introduction/8.3 TensorFlow Minimal Example - Exercise 3 - Solution.html
160 B
5. TensorFlow - An introduction/8.4 TensorFlow Minimal Example - All Exercises.html
154 B
5. TensorFlow - An introduction/8.5 TensorFlow Minimal Example - Exercise 2_2 - 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.srt
2.4 kB
6. Going deeper Introduction to deep neural networks/1.1 Course Notes - Section 6.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.srt
3.3 kB
6. Going deeper Introduction to deep neural networks/2.1 Course Notes - Section 6.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.srt
6.7 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.srt
3.8 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.srt
5.2 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.srt
4.3 kB
6. Going deeper Introduction to deep neural networks/7. Backpropagation.mp4
11 MB
6. Going deeper Introduction to deep neural networks/7. Backpropagation.srt
4.4 kB
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.srt
4.0 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
182 kB
8. Overfitting/1. Underfitting and overfitting.mp4
11 MB
8. Overfitting/1. Underfitting and overfitting.srt
5.6 kB
8. Overfitting/2. Underfitting and overfitting - classification.mp4
6.8 MB
8. Overfitting/2. Underfitting and overfitting - classification.srt
2.7 kB
8. Overfitting/3. Training and validation.mp4
9.2 MB
8. Overfitting/3. Training and validation.srt
4.9 kB
8. Overfitting/4. Training, validation, and test.mp4
7.4 MB
8. Overfitting/4. Training, validation, and test.srt
3.6 kB
8. Overfitting/5. N-fold cross validation.mp4
7.0 MB
8. Overfitting/5. N-fold cross validation.srt
4.2 kB
8. Overfitting/6. Early stopping.mp4
9.4 MB
8. Overfitting/6. Early stopping.srt
6.9 kB
9. Initialization/1. Initialization - Introduction.mp4
8.0 MB
9. Initialization/1. Initialization - Introduction.srt
3.5 kB
9. Initialization/2. Types of simple initializations.mp4
5.6 MB
9. Initialization/2. Types of simple initializations.srt
3.7 kB
9. Initialization/3. Xavier initialization.mp4
5.8 MB
9. Initialization/3. Xavier initialization.srt
3.7 kB
[CourseClub.Me].url
48 B
[DesireCourse.Net].url
51 B
[FreeCourseWorld.Com].url
54 B