[FreeAllCourse.Com] Udemy - Deep Learning A-Z™ Hands-On Artificial Neural Networks

Creation Time	Aug. 19, 2023, 11:55 a.m.
Last Access Time	Oct. 18, 2024, 3:56 a.m.
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Keywords	A-Z™ Neural Hands-On - FreeAllCourse Deep Udemy Artificial Learning Com Networks
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Total Files	349
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1. Welcome to the course/6.1 DL Colab Changes.zip 280.0 MB
23. Building a Boltzmann Machine/8. Building a Boltzmann Machine - Step 4.mp4 64.5 MB
18. SOMs Intuition/8. Reading an Advanced SOM.mp4 61.9 MB
23. Building a Boltzmann Machine/17. Building a Boltzmann Machine - Step 13.mp4 58.5 MB
6. Evaluating, Improving and Tuning the ANN/1. Evaluating the ANN.mp4 55.8 MB
23. Building a Boltzmann Machine/18. Building a Boltzmann Machine - Step 14.mp4 54.1 MB
14. RNN Intuition/6. Practical intuition.mp4 52.9 MB
26. Building an AutoEncoder/16. THANK YOU bonus video.mp4 52.3 MB
26. Building an AutoEncoder/10. Building an AutoEncoder - Step 6.mp4 52.1 MB
6. Evaluating, Improving and Tuning the ANN/3. Tuning the ANN.mp4 50.8 MB
26. Building an AutoEncoder/8. Building an AutoEncoder - Step 4.mp4 49.6 MB
20. Mega Case Study/3. Mega Case Study - Step 3.mp4 49.3 MB
10. Building a CNN/12. Building a CNN - Step 9.mp4 46.9 MB
14. RNN Intuition/5. LSTMs.mp4 46.0 MB
4. Building an ANN/6. Building an ANN - Step 2.mp4 45.9 MB
9. CNN Intuition/8. Step 4 - Full Connection.mp4 42.8 MB
30. Classification Template/5. Logistic Regression Implementation - Step 5.mp4 42.5 MB
23. Building a Boltzmann Machine/16. Building a Boltzmann Machine - Step 12.srt 41.6 MB
23. Building a Boltzmann Machine/16. Building a Boltzmann Machine - Step 12.mp4 41.6 MB
11. Homework - What's that pet/2. Homework Solution.mp4 41.0 MB
9. CNN Intuition/6. Step 2 - Pooling.mp4 40.2 MB
15. Building a RNN/15. Building a RNN - Step 13.mp4 39.9 MB
23. Building a Boltzmann Machine/12. Building a Boltzmann Machine - Step 8.mp4 39.4 MB
22. Boltzmann Machine Intuition/5. Restricted Boltzmann Machine.mp4 39.3 MB
5. Homework Challenge - Should we say goodbye to that customer/2. Homework Solution.mp4 37.6 MB
14. RNN Intuition/3. The idea behind Recurrent Neural Networks.mp4 37.3 MB
15. Building a RNN/6. Building a RNN - Step 4.mp4 37.1 MB
26. Building an AutoEncoder/4. Building an AutoEncoder - Step 1.mp4 36.7 MB
19. Building a SOM/4. Building a SOM - Step 3.mp4 36.0 MB
23. Building a Boltzmann Machine/3. Building a Boltzmann Machine - Introduction.mp4 34.1 MB
26. Building an AutoEncoder/12. Building an AutoEncoder - Step 8.mp4 33.8 MB
26. Building an AutoEncoder/11. Building an AutoEncoder - Step 7.mp4 33.7 MB
9. CNN Intuition/10. Softmax & Cross-Entropy.mp4 33.2 MB
23. Building a Boltzmann Machine/14. Building a Boltzmann Machine - Step 10.mp4 33.2 MB
22. Boltzmann Machine Intuition/2. Boltzmann Machine.mp4 31.9 MB
26. Building an AutoEncoder/13. Building an AutoEncoder - Step 9.mp4 31.6 MB
1. Welcome to the course/1. What is Deep Learning.mp4 31.3 MB
23. Building a Boltzmann Machine/11. Building a Boltzmann Machine - Step 7.mp4 31.2 MB
18. SOMs Intuition/5. How do Self-Organizing Maps Learn (Part 1).mp4 31.1 MB
9. CNN Intuition/4. Step 1 - Convolution Operation.mp4 31.0 MB
20. Mega Case Study/4. Mega Case Study - Step 4.mp4 30.9 MB
19. Building a SOM/2. Building a SOM - Step 1.mp4 30.7 MB
23. Building a Boltzmann Machine/5. Building a Boltzmann Machine - Step 1.mp4 30.5 MB
4. Building an ANN/9. Building an ANN - Step 5.mp4 29.6 MB
3. ANN Intuition/2. The Neuron.mp4 29.6 MB
23. Building a Boltzmann Machine/6. Building a Boltzmann Machine - Step 2.mp4 29.6 MB
22. Boltzmann Machine Intuition/6. Contrastive Divergence.mp4 29.6 MB
9. CNN Intuition/3. What are convolutional neural networks.mp4 29.5 MB
15. Building a RNN/13. Building a RNN - Step 11.mp4 29.3 MB
28. Regression & Classification Intuition/5. Logistic Regression Intuition.mp4 29.2 MB
14. RNN Intuition/4. The Vanishing Gradient Problem.mp4 29.0 MB
29. Data Preprocessing Template/4. Data Preprocessing - Step 4.mp4 29.0 MB
19. Building a SOM/5. Building a SOM - Step 4.mp4 28.7 MB
26. Building an AutoEncoder/15. Building an AutoEncoder - Step 11.mp4 28.3 MB
25. AutoEncoders Intuition/2. Auto Encoders.mp4 28.2 MB
26. Building an AutoEncoder/5. Building an AutoEncoder - Step 2.mp4 27.8 MB
22. Boltzmann Machine Intuition/4. Editing Wikipedia - Our Contribution to the World.mp4 27.3 MB
10. Building a CNN/7. Building a CNN - Step 4.mp4 27.2 MB
3. ANN Intuition/5. How do Neural Networks learn.mp4 26.6 MB
15. Building a RNN/7. Building a RNN - Step 5.mp4 26.2 MB
23. Building a Boltzmann Machine/7. Building a Boltzmann Machine - Step 3.mp4 26.0 MB
23. Building a Boltzmann Machine/10. Building a Boltzmann Machine - Step 6.mp4 25.2 MB
18. SOMs Intuition/4. K-Means Clustering (Refresher).mp4 25.0 MB
4. Building an ANN/5. Building an ANN - Step 1.mp4 24.3 MB
3. ANN Intuition/4. How do Neural Networks work.mp4 23.5 MB
29. Data Preprocessing Template/5. Data Preprocessing - Step 5.mp4 22.9 MB
29. Data Preprocessing Template/6. Data Preprocessing - Step 6.mp4 22.8 MB
23. Building a Boltzmann Machine/15. Building a Boltzmann Machine - Step 11.mp4 22.4 MB
18. SOMs Intuition/10. EXTRA K-means Clustering (part 3).mp4 21.8 MB
29. Data Preprocessing Template/3. Data Preprocessing - Step 3.mp4 21.7 MB
15. Building a RNN/17. Building a RNN - Step 15.mp4 21.7 MB
15. Building a RNN/16. Building a RNN - Step 14.mp4 21.5 MB
15. Building a RNN/9. Building a RNN - Step 7.mp4 20.8 MB
10. Building a CNN/13. Building a CNN - Step 10.mp4 20.5 MB
1. Welcome to the course/2. Updates on Udemy Reviews.mp4 20.4 MB
23. Building a Boltzmann Machine/13. Building a Boltzmann Machine - Step 9.mp4 20.4 MB
1. Welcome to the course/4. Installing Python.mp4 20.4 MB
26. Building an AutoEncoder/6. Building an AutoEncoder - Step 3.mp4 20.1 MB
18. SOMs Intuition/2. How do Self-Organizing Maps Work.mp4 20.0 MB
6. Evaluating, Improving and Tuning the ANN/2. Improving the ANN.mp4 19.8 MB
19. Building a SOM/3. Building a SOM - Step 2.mp4 19.4 MB
10. Building a CNN/4. Building a CNN - Step 1.mp4 19.2 MB
18. SOMs Intuition/6. How do Self-Organizing Maps Learn (Part 2).mp4 18.7 MB
18. SOMs Intuition/7. Live SOM example.mp4 18.6 MB
3. ANN Intuition/6. Gradient Descent.mp4 18.5 MB
22. Boltzmann Machine Intuition/3. Energy-Based Models (EBM).mp4 18.5 MB
4. Building an ANN/12. Building an ANN - Step 8.mp4 18.2 MB
4. Building an ANN/14. Building an ANN - Step 10.mp4 17.4 MB
4. Building an ANN/13. Building an ANN - Step 9.mp4 16.9 MB
3. ANN Intuition/7. Stochastic Gradient Descent.mp4 16.8 MB
4. Building an ANN/3. Business Problem Description.mp4 16.4 MB
15. Building a RNN/5. Building a RNN - Step 3.mp4 15.9 MB
29. Data Preprocessing Template/2. Data Preprocessing - Step 2.mp4 15.9 MB
15. Building a RNN/4. Building a RNN - Step 2.mp4 15.6 MB
23. Building a Boltzmann Machine/9. Building a Boltzmann Machine - Step 5.mp4 15.5 MB
3. ANN Intuition/3. The Activation Function.mp4 14.8 MB
4. Building an ANN/9. Building an ANN - Step 5.srt 14.4 MB
9. CNN Intuition/5. Step 1(b) - ReLU Layer.mp4 14.1 MB
25. AutoEncoders Intuition/6. Sparse Autoencoders.mp4 14.0 MB
15. Building a RNN/3. Building a RNN - Step 1.mp4 13.7 MB
25. AutoEncoders Intuition/4. Training an Auto Encoder.mp4 13.6 MB
15. Building a RNN/14. Building a RNN - Step 12.mp4 13.5 MB
15. Building a RNN/10. Building a RNN - Step 8.mp4 13.4 MB
20. Mega Case Study/2. Mega Case Study - Step 2.mp4 13.4 MB
29. Data Preprocessing Template/1. Data Preprocessing - Step 1.mp4 13.3 MB
22. Boltzmann Machine Intuition/7. Deep Belief Networks.mp4 12.6 MB
10. Building a CNN/10. Building a CNN - Step 7.mp4 12.6 MB
18. SOMs Intuition/9. EXTRA K-means Clustering (part 2).mp4 12.3 MB
30. Classification Template/1. Logistic Regression Implementation - Step 1.mp4 12.2 MB
26. Building an AutoEncoder/9. Building an AutoEncoder - Step 5.mp4 11.9 MB
30. Classification Template/6. Classification Template.mp4 11.7 MB
15. Building a RNN/12. Building a RNN - Step 10.mp4 11.4 MB
26. Building an AutoEncoder/14. Building an AutoEncoder - Step 10.mp4 11.3 MB
3. ANN Intuition/8. Backpropagation.mp4 10.9 MB
10. Building a CNN/8. Building a CNN - Step 5.mp4 9.9 MB
10. Building a CNN/9. Building a CNN - Step 6.mp4 9.7 MB
30. Classification Template/4. Logistic Regression Implementation - Step 4.mp4 9.7 MB
28. Regression & Classification Intuition/2. Simple Linear Regression Intuition - Step 1.mp4 9.5 MB
4. Building an ANN/11. Building an ANN - Step 7.mp4 9.0 MB
4. Building an ANN/7. Building an ANN - Step 3.mp4 8.4 MB
15. Building a RNN/11. Building a RNN - Step 9.mp4 8.2 MB
30. Classification Template/2. Logistic Regression Implementation - Step 2.mp4 8.1 MB
29. Data Preprocessing Template/7. Data Preprocessing Template.mp4 8.1 MB
9. CNN Intuition/9. Summary.mp4 7.9 MB
10. Building a CNN/3. Introduction to CNNs.mp4 7.9 MB
25. AutoEncoders Intuition/5. Overcomplete hidden layers.mp4 7.6 MB
14. RNN Intuition/7. EXTRA LSTM Variations.mp4 7.3 MB
4. Building an ANN/10. Building an ANN - Step 6.mp4 7.1 MB
10. Building a CNN/11. Building a CNN - Step 8.mp4 6.8 MB
15. Building a RNN/8. Building a RNN - Step 6.mp4 6.8 MB
15. Building a RNN/1. How to get the dataset.mp4 6.5 MB
1. Welcome to the course/5. How to get the dataset.mp4 6.5 MB
10. Building a CNN/1. How to get the dataset.mp4 6.5 MB
19. Building a SOM/1. How to get the dataset.mp4 6.5 MB
23. Building a Boltzmann Machine/1. How to get the dataset.mp4 6.5 MB
26. Building an AutoEncoder/1. How to get the dataset.mp4 6.5 MB
4. Building an ANN/2. How to get the dataset.srt 6.5 MB
4. Building an ANN/2. How to get the dataset.mp4 6.5 MB
30. Classification Template/3. Logistic Regression Implementation - Step 3.mp4 6.0 MB
4. Building an ANN/8. Building an ANN - Step 4.mp4 6.0 MB
9. CNN Intuition/2. Plan of attack.mp4 5.9 MB
10. Building a CNN/5. Building a CNN - Step 2.mp4 5.9 MB
22. Boltzmann Machine Intuition/8. Deep Boltzmann Machines.mp4 5.9 MB
25. AutoEncoders Intuition/7. Denoising Autoencoders.mp4 5.7 MB
20. Mega Case Study/1. Mega Case Study - Step 1.mp4 5.4 MB
28. Regression & Classification Intuition/3. Simple Linear Regression Intuition - Step 2.mp4 5.4 MB
25. AutoEncoders Intuition/8. Contractive Autoencoders.mp4 5.3 MB
18. SOMs Intuition/1. Plan of attack.mp4 5.2 MB
3. ANN Intuition/1. Plan of Attack.mp4 4.7 MB
25. AutoEncoders Intuition/9. Stacked Autoencoders.mp4 4.5 MB
14. RNN Intuition/2. Plan of attack.mp4 4.2 MB
25. AutoEncoders Intuition/1. Plan of attack.mp4 4.1 MB
18. SOMs Intuition/3. Why revisit K-Means.mp4 4.0 MB
22. Boltzmann Machine Intuition/1. Plan of attack.mp4 3.8 MB
25. AutoEncoders Intuition/10. Deep Autoencoders.mp4 3.3 MB
9. CNN Intuition/7. Step 3 - Flattening.mp4 3.3 MB
25. AutoEncoders Intuition/3. A Note on Biases.mp4 2.4 MB
10. Building a CNN/6. Building a CNN - Step 3.mp4 2.2 MB
28. Regression & Classification Intuition/4. Multiple Linear Regression Intuition.mp4 1.8 MB
23. Building a Boltzmann Machine/8. Building a Boltzmann Machine - Step 4.srt 42.5 KB
26. Building an AutoEncoder/8. Building an AutoEncoder - Step 4.srt 41.1 KB
6. Evaluating, Improving and Tuning the ANN/1. Evaluating the ANN.srt 40.1 KB
10. Building a CNN/12. Building a CNN - Step 9.srt 39.6 KB
14. RNN Intuition/5. LSTMs.srt 39.3 KB
9. CNN Intuition/8. Step 4 - Full Connection.srt 38.6 KB
22. Boltzmann Machine Intuition/5. Restricted Boltzmann Machine.srt 37.8 KB
6. Evaluating, Improving and Tuning the ANN/3. Tuning the ANN.srt 36.6 KB
23. Building a Boltzmann Machine/17. Building a Boltzmann Machine - Step 13.srt 35.9 KB
4. Building an ANN/6. Building an ANN - Step 2.srt 35.9 KB
3. ANN Intuition/2. The Neuron.srt 35.8 KB
19. Building a SOM/4. Building a SOM - Step 3.srt 35.2 KB
30. Classification Template/5. Logistic Regression Implementation - Step 5.srt 35.0 KB
26. Building an AutoEncoder/10. Building an AutoEncoder - Step 6.srt 34.7 KB
9. CNN Intuition/10. Softmax & Cross-Entropy.srt 34.6 KB
23. Building a Boltzmann Machine/18. Building a Boltzmann Machine - Step 14.srt 34.2 KB
28. Regression & Classification Intuition/5. Logistic Regression Intuition.srt 32.7 KB
9. CNN Intuition/4. Step 1 - Convolution Operation.srt 32.2 KB
14. RNN Intuition/3. The idea behind Recurrent Neural Networks.srt 31.7 KB
26. Building an AutoEncoder/12. Building an AutoEncoder - Step 8.srt 31.1 KB
9. CNN Intuition/3. What are convolutional neural networks.srt 31.1 KB
22. Boltzmann Machine Intuition/6. Contrastive Divergence.srt 31.0 KB
15. Building a RNN/15. Building a RNN - Step 13.srt 30.9 KB
18. SOMs Intuition/4. K-Means Clustering (Refresher).srt 30.9 KB
11. Homework - What's that pet/2. Homework Solution.srt 30.8 KB
22. Boltzmann Machine Intuition/2. Boltzmann Machine.srt 30.2 KB
14. RNN Intuition/4. The Vanishing Gradient Problem.srt 29.7 KB
18. SOMs Intuition/5. How do Self-Organizing Maps Learn (Part 1).srt 29.1 KB
18. SOMs Intuition/8. Reading an Advanced SOM.srt 28.5 KB
9. CNN Intuition/6. Step 2 - Pooling.srt 28.5 KB
14. RNN Intuition/6. Practical intuition.srt 28.0 KB
20. Mega Case Study/3. Mega Case Study - Step 3.srt 27.7 KB
26. Building an AutoEncoder/11. Building an AutoEncoder - Step 7.srt 27.6 KB
3. ANN Intuition/5. How do Neural Networks learn.srt 27.4 KB
26. Building an AutoEncoder/13. Building an AutoEncoder - Step 9.srt 27.2 KB
10. Building a CNN/7. Building a CNN - Step 4.srt 26.7 KB
4. Building an ANN/5. Building an ANN - Step 1.srt 26.6 KB
3. ANN Intuition/4. How do Neural Networks work.srt 26.3 KB
19. Building a SOM/2. Building a SOM - Step 1.srt 26.2 KB
15. Building a RNN/6. Building a RNN - Step 4.srt 25.3 KB
18. SOMs Intuition/10. EXTRA K-means Clustering (part 3).srt 25.0 KB
23. Building a Boltzmann Machine/12. Building a Boltzmann Machine - Step 8.srt 24.8 KB
29. Data Preprocessing Template/4. Data Preprocessing - Step 4.srt 24.0 KB
26. Building an AutoEncoder/5. Building an AutoEncoder - Step 2.srt 24.0 KB
26. Building an AutoEncoder/15. Building an AutoEncoder - Step 11.srt 23.9 KB
1. Welcome to the course/1. What is Deep Learning.srt 23.9 KB
26. Building an AutoEncoder/4. Building an AutoEncoder - Step 1.srt 23.1 KB
23. Building a Boltzmann Machine/14. Building a Boltzmann Machine - Step 10.srt 22.6 KB
22. Boltzmann Machine Intuition/3. Energy-Based Models (EBM).srt 21.8 KB
25. AutoEncoders Intuition/2. Auto Encoders.srt 21.4 KB
19. Building a SOM/5. Building a SOM - Step 4.srt 21.4 KB
20. Mega Case Study/4. Mega Case Study - Step 4.srt 21.4 KB
29. Data Preprocessing Template/6. Data Preprocessing - Step 6.srt 21.4 KB
29. Data Preprocessing Template/5. Data Preprocessing - Step 5.srt 21.2 KB
5. Homework Challenge - Should we say goodbye to that customer/2. Homework Solution.srt 21.2 KB
23. Building a Boltzmann Machine/11. Building a Boltzmann Machine - Step 7.srt 20.8 KB
23. Building a Boltzmann Machine/3. Building a Boltzmann Machine - Introduction.srt 20.5 KB
15. Building a RNN/7. Building a RNN - Step 5.srt 19.7 KB
29. Data Preprocessing Template/3. Data Preprocessing - Step 3.srt 19.4 KB
19. Building a SOM/3. Building a SOM - Step 2.srt 19.2 KB
3. ANN Intuition/6. Gradient Descent.srt 19.1 KB
15. Building a RNN/13. Building a RNN - Step 11.srt 18.6 KB
10. Building a CNN/4. Building a CNN - Step 1.srt 18.5 KB
23. Building a Boltzmann Machine/5. Building a Boltzmann Machine - Step 1.srt 18.5 KB
23. Building a Boltzmann Machine/6. Building a Boltzmann Machine - Step 2.srt 18.4 KB
18. SOMs Intuition/6. How do Self-Organizing Maps Learn (Part 2).srt 18.4 KB
18. SOMs Intuition/2. How do Self-Organizing Maps Work.srt 18.3 KB
15. Building a RNN/17. Building a RNN - Step 15.srt 17.7 KB
3. ANN Intuition/7. Stochastic Gradient Descent.srt 17.6 KB
10. Building a CNN/13. Building a CNN - Step 10.srt 17.3 KB
18. SOMs Intuition/9. EXTRA K-means Clustering (part 2).srt 17.1 KB
3. ANN Intuition/3. The Activation Function.srt 16.9 KB
23. Building a Boltzmann Machine/7. Building a Boltzmann Machine - Step 3.srt 16.4 KB
1. Welcome to the course/4. Installing Python.srt 16.3 KB
26. Building an AutoEncoder/6. Building an AutoEncoder - Step 3.srt 16.2 KB
23. Building a Boltzmann Machine/10. Building a Boltzmann Machine - Step 6.srt 16.0 KB
15. Building a RNN/9. Building a RNN - Step 7.srt 15.9 KB
29. Data Preprocessing Template/1. Data Preprocessing - Step 1.srt 15.3 KB
4. Building an ANN/12. Building an ANN - Step 8.srt 15.2 KB
29. Data Preprocessing Template/2. Data Preprocessing - Step 2.srt 15.2 KB
15. Building a RNN/16. Building a RNN - Step 14.srt 14.1 KB
4. Building an ANN/14. Building an ANN - Step 10.srt 14.0 KB
6. Evaluating, Improving and Tuning the ANN/2. Improving the ANN.srt 13.7 KB
23. Building a Boltzmann Machine/13. Building a Boltzmann Machine - Step 9.srt 13.6 KB
25. AutoEncoders Intuition/4. Training an Auto Encoder.srt 13.4 KB
23. Building a Boltzmann Machine/15. Building a Boltzmann Machine - Step 11.srt 12.8 KB
15. Building a RNN/4. Building a RNN - Step 2.srt 12.7 KB
9. CNN Intuition/5. Step 1(b) - ReLU Layer.srt 12.5 KB
10. Building a CNN/10. Building a CNN - Step 7.srt 12.4 KB
25. AutoEncoders Intuition/6. Sparse Autoencoders.srt 12.2 KB
15. Building a RNN/3. Building a RNN - Step 1.srt 12.0 KB
4. Building an ANN/13. Building an ANN - Step 9.srt 11.8 KB
15. Building a RNN/10. Building a RNN - Step 8.srt 11.4 KB
28. Regression & Classification Intuition/2. Simple Linear Regression Intuition - Step 1.srt 11.2 KB
22. Boltzmann Machine Intuition/7. Deep Belief Networks.srt 10.6 KB
15. Building a RNN/5. Building a RNN - Step 3.srt 10.5 KB
23. Building a Boltzmann Machine/9. Building a Boltzmann Machine - Step 5.srt 10.4 KB
10. Building a CNN/9. Building a CNN - Step 6.srt 10.3 KB
4. Building an ANN/3. Business Problem Description.srt 10.3 KB
3. ANN Intuition/8. Backpropagation.srt 9.9 KB
26. Building an AutoEncoder/9. Building an AutoEncoder - Step 5.srt 9.9 KB
10. Building a CNN/8. Building a CNN - Step 5.srt 9.8 KB
30. Classification Template/1. Logistic Regression Implementation - Step 1.srt 9.8 KB
15. Building a RNN/14. Building a RNN - Step 12.srt 9.4 KB
15. Building a RNN/12. Building a RNN - Step 10.srt 9.3 KB
26. Building an AutoEncoder/14. Building an AutoEncoder - Step 10.srt 9.3 KB
18. SOMs Intuition/7. Live SOM example.srt 9.1 KB
20. Mega Case Study/2. Mega Case Study - Step 2.srt 8.7 KB
10. Building a CNN/3. Introduction to CNNs.srt 8.6 KB
9. CNN Intuition/9. Summary.srt 8.5 KB
30. Classification Template/6. Classification Template.srt 8.2 KB
30. Classification Template/4. Logistic Regression Implementation - Step 4.srt 8.1 KB
25. AutoEncoders Intuition/5. Overcomplete hidden layers.srt 8.1 KB
4. Building an ANN/11. Building an ANN - Step 7.srt 7.9 KB
29. Data Preprocessing Template/7. Data Preprocessing Template.srt 7.9 KB
9. CNN Intuition/2. Plan of attack.srt 7.4 KB
14. RNN Intuition/7. EXTRA LSTM Variations.srt 6.8 KB
20. Mega Case Study/1. Mega Case Study - Step 1.srt 6.7 KB
22. Boltzmann Machine Intuition/4. Editing Wikipedia - Our Contribution to the World.srt 6.6 KB
18. SOMs Intuition/1. Plan of attack.srt 6.6 KB
15. Building a RNN/11. Building a RNN - Step 9.srt 6.5 KB
4. Building an ANN/7. Building an ANN - Step 3.srt 6.5 KB
22. Boltzmann Machine Intuition/8. Deep Boltzmann Machines.srt 6.3 KB
15. Building a RNN/8. Building a RNN - Step 6.srt 6.1 KB
30. Classification Template/2. Logistic Regression Implementation - Step 2.srt 6.0 KB
4. Building an ANN/10. Building an ANN - Step 6.srt 6.0 KB
28. Regression & Classification Intuition/3. Simple Linear Regression Intuition - Step 2.srt 6.0 KB
10. Building a CNN/5. Building a CNN - Step 2.srt 5.7 KB
10. Building a CNN/11. Building a CNN - Step 8.srt 5.6 KB
3. ANN Intuition/1. Plan of Attack.srt 5.6 KB
25. AutoEncoders Intuition/7. Denoising Autoencoders.srt 5.2 KB
22. Boltzmann Machine Intuition/1. Plan of attack.srt 5.2 KB
30. Classification Template/3. Logistic Regression Implementation - Step 3.srt 5.0 KB
25. AutoEncoders Intuition/8. Contractive Autoencoders.srt 4.9 KB
14. RNN Intuition/2. Plan of attack.srt 4.8 KB
18. SOMs Intuition/3. Why revisit K-Means.srt 4.8 KB
25. AutoEncoders Intuition/1. Plan of attack.srt 4.7 KB
4. Building an ANN/8. Building an ANN - Step 4.srt 4.5 KB
23. Building a Boltzmann Machine/19. Evaluating the Boltzmann Machine.html 4.5 KB
25. AutoEncoders Intuition/10. Deep Autoencoders.srt 3.8 KB
9. CNN Intuition/7. Step 3 - Flattening.srt 3.8 KB
1. Welcome to the course/5. How to get the dataset.srt 3.5 KB
10. Building a CNN/1. How to get the dataset.srt 3.5 KB
15. Building a RNN/1. How to get the dataset.srt 3.5 KB
19. Building a SOM/1. How to get the dataset.srt 3.5 KB
23. Building a Boltzmann Machine/1. How to get the dataset.srt 3.5 KB
26. Building an AutoEncoder/1. How to get the dataset.srt 3.5 KB
25. AutoEncoders Intuition/9. Stacked Autoencoders.srt 3.3 KB
31. Bonus Lectures/1. YOUR SPECIAL BONUS.html 3.0 KB
25. AutoEncoders Intuition/3. A Note on Biases.srt 2.7 KB
26. Building an AutoEncoder/16. THANK YOU bonus video.srt 2.4 KB
10. Building a CNN/6. Building a CNN - Step 3.srt 2.4 KB
1. Welcome to the course/6.2 DL-A-Z-Colab-Run-Instructions.ipynb.zip 2.2 KB
28. Regression & Classification Intuition/4. Multiple Linear Regression Intuition.srt 2.2 KB
1. Welcome to the course/2. Updates on Udemy Reviews.srt 1.8 KB
1. Welcome to the course/3. BONUS Learning Paths.html 1.8 KB
1. Welcome to the course/9. FAQBot!.html 1.8 KB
16. Evaluating, Improving and Tuning the RNN/1. Evaluating the RNN.html 1.7 KB
21. ------------------------- Part 5 - Boltzmann Machines -------------------------/1. Welcome to Part 5 - Boltzmann Machines.html 1.6 KB
26. Building an AutoEncoder/7. Homework Challenge - Coding Exercise.html 1.5 KB
4. Building an ANN/4. Installing Keras.html 1.4 KB
26. Building an AutoEncoder/2. Installing PyTorch.html 1.4 KB
23. Building a Boltzmann Machine/2. Installing PyTorch.html 1.4 KB
4. Building an ANN/1. Prerequisites.html 1.3 KB
16. Evaluating, Improving and Tuning the RNN/2. Improving the RNN.html 1.3 KB
1. Welcome to the course/7. BONUS Meet Your Instructors.html 1.2 KB
Verify Files.txt 1.0 KB
13. ---------------------- Part 3 - Recurrent Neural Networks ----------------------/1. Welcome to Part 3 - Recurrent Neural Networks.html 1.0 KB
24. ---------------------------- Part 6 - AutoEncoders ----------------------------/1. Welcome to Part 6 - AutoEncoders.html 1.0 KB
10. Building a CNN/2. Installing Keras.html 927 bytes
15. Building a RNN/2. Installing Keras.html 927 bytes
12. Evaluating, Improving and Tuning the CNN/1. Homework Challenge - Get the gold medal.html 917 bytes
27. ------------------- Annex - Get the Machine Learning Basics -------------------/1. Annex - Get the Machine Learning Basics.html 873 bytes
11. Homework - What's that pet/1. Homework Instruction.html 838 bytes
16. Evaluating, Improving and Tuning the RNN/3. Tuning the RNN.html 693 bytes
5. Homework Challenge - Should we say goodbye to that customer/1. Homework Instruction.html 682 bytes
1. Welcome to the course/6. Colab File.html 665 bytes
28. Regression & Classification Intuition/1. What You Need for Regression & Classification.html 648 bytes
1. Welcome to the course/8. Some Additional Resources!!.html 611 bytes
2. --------------------- Part 1 - Artificial Neural Networks ---------------------/1. Welcome to Part 1 - Artificial Neural Networks.html 516 bytes
7. Homework Challenge - Put me one step down on the podium/1. Homework Instruction.html 426 bytes
9. CNN Intuition/1. What You'll Need for CNN.html 386 bytes
14. RNN Intuition/1. What You'll Need for RNN.html 366 bytes
23. Building a Boltzmann Machine/4. Same Data Preprocessing in Parts 5 and 6.html 349 bytes
26. Building an AutoEncoder/3. Same Data Preprocessing in Parts 5 and 6.html 348 bytes
17. ------------------------ Part 4 - Self Organizing Maps ------------------------/1. Welcome to Part 4 - Self Organizing Maps.html 333 bytes
8. -------------------- Part 2 - Convolutional Neural Networks --------------------/1. Welcome to Part 2 - Convolutional Neural Networks.html 323 bytes
12. Evaluating, Improving and Tuning the CNN/2. Homework Challenge Solution - Get the gold medal.html 185 bytes
0. Websites you may like/[FreeAllCourse.Com].url 52 bytes
[FreeAllCourse.Com].url 52 bytes

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