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[DesireCourse.Net] Udemy - Deep Learning A-Z™ Hands-On Artificial Neural Networks
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文档列表
1. Welcome to the course/1. Updates on Udemy Reviews.mp4
64.1 MB
6. Evaluating, Improving and Tuning the ANN/1. Evaluating the ANN.mp4
58.5 MB
14. RNN Intuition/6. Practical intuition.mp4
55.4 MB
26. Building an AutoEncoder/16. THANK YOU bonus video.mp4
54.8 MB
6. Evaluating, Improving and Tuning the ANN/3. Tuning the ANN.mp4
53.2 MB
26. Building an AutoEncoder/8. Building an AutoEncoder - Step 4.mp4
52.0 MB
10. Building a CNN/12. Building a CNN - Step 9.mp4
49.1 MB
14. RNN Intuition/5. LSTMs.mp4
48.2 MB
4. Building an ANN/6. Building an ANN - Step 2.mp4
48.1 MB
23. Building a Boltzmann Machine/8. Building a Boltzmann Machine - Step 4.mp4
47.9 MB
18. SOMs Intuition/8. Reading an Advanced SOM.mp4
45.3 MB
23. Building a Boltzmann Machine/17. Building a Boltzmann Machine - Step 13.mp4
45.1 MB
9. CNN Intuition/8. Step 4 - Full Connection.mp4
44.8 MB
30. Classification Template/5. Logistic Regression Implementation - Step 5.mp4
44.5 MB
11. Homework - What's that pet/2. Homework Solution.mp4
43.0 MB
23. Building a Boltzmann Machine/18. Building a Boltzmann Machine - Step 14.mp4
42.4 MB
9. CNN Intuition/6. Step 2 - Pooling.mp4
42.2 MB
15. Building a RNN/15. Building a RNN - Step 13.mp4
41.8 MB
26. Building an AutoEncoder/10. Building an AutoEncoder - Step 6.mp4
39.8 MB
5. Homework Challenge - Should we say goodbye to that customer/2. Homework Solution.mp4
39.5 MB
14. RNN Intuition/3. The idea behind Recurrent Neural Networks.mp4
39.1 MB
15. Building a RNN/6. Building a RNN - Step 4.mp4
38.9 MB
19. Building a SOM/4. Building a SOM - Step 3.mp4
37.8 MB
20. Mega Case Study/3. Mega Case Study - Step 3.mp4
36.9 MB
26. Building an AutoEncoder/12. Building an AutoEncoder - Step 8.mp4
35.5 MB
26. Building an AutoEncoder/11. Building an AutoEncoder - Step 7.mp4
35.3 MB
9. CNN Intuition/10. Softmax & Cross-Entropy.mp4
34.9 MB
22. Boltzmann Machine Intuition/5. Restricted Boltzmann Machine.mp4
33.4 MB
26. Building an AutoEncoder/13. Building an AutoEncoder - Step 9.mp4
33.1 MB
1. Welcome to the course/2. What is Deep Learning.mp4
32.8 MB
9. CNN Intuition/4. Step 1 - Convolution Operation.mp4
32.5 MB
23. Building a Boltzmann Machine/16. Building a Boltzmann Machine - Step 12.mp4
32.5 MB
19. Building a SOM/2. Building a SOM - Step 1.mp4
32.2 MB
4. Building an ANN/9. Building an ANN - Step 5.mp4
31.0 MB
3. ANN Intuition/2. The Neuron.mp4
31.0 MB
9. CNN Intuition/3. What are convolutional neural networks.mp4
30.9 MB
15. Building a RNN/13. Building a RNN - Step 11.mp4
30.7 MB
23. Building a Boltzmann Machine/12. Building a Boltzmann Machine - Step 8.mp4
30.6 MB
28. Regression & Classification Intuition/5. Logistic Regression Intuition.mp4
30.6 MB
14. RNN Intuition/4. The Vanishing Gradient Problem.mp4
30.4 MB
29. Data Preprocessing Template/4. Data Preprocessing - Step 4.mp4
30.4 MB
19. Building a SOM/5. Building a SOM - Step 4.mp4
30.1 MB
26. Building an AutoEncoder/15. Building an AutoEncoder - Step 11.mp4
29.7 MB
26. Building an AutoEncoder/5. Building an AutoEncoder - Step 2.mp4
29.2 MB
10. Building a CNN/7. Building a CNN - Step 4.mp4
28.5 MB
3. ANN Intuition/5. How do Neural Networks learn.mp4
27.8 MB
15. Building a RNN/7. Building a RNN - Step 5.mp4
27.5 MB
26. Building an AutoEncoder/4. Building an AutoEncoder - Step 1.mp4
27.3 MB
18. SOMs Intuition/5. How do Self-Organizing Maps Learn (Part 1).mp4
26.3 MB
22. Boltzmann Machine Intuition/2. Boltzmann Machine.mp4
26.2 MB
22. Boltzmann Machine Intuition/6. Contrastive Divergence.mp4
26.1 MB
23. Building a Boltzmann Machine/14. Building a Boltzmann Machine - Step 10.mp4
25.6 MB
4. Building an ANN/5. Building an ANN - Step 1.mp4
25.5 MB
3. ANN Intuition/4. How do Neural Networks work.mp4
24.7 MB
23. Building a Boltzmann Machine/11. Building a Boltzmann Machine - Step 7.mp4
24.0 MB
29. Data Preprocessing Template/5. Data Preprocessing - Step 5.mp4
24.0 MB
29. Data Preprocessing Template/6. Data Preprocessing - Step 6.mp4
23.9 MB
20. Mega Case Study/4. Mega Case Study - Step 4.mp4
23.8 MB
29. Data Preprocessing Template/3. Data Preprocessing - Step 3.mp4
22.8 MB
15. Building a RNN/17. Building a RNN - Step 15.mp4
22.7 MB
25. AutoEncoders Intuition/2. Auto Encoders.mp4
22.6 MB
15. Building a RNN/16. Building a RNN - Step 14.mp4
22.6 MB
18. SOMs Intuition/4. K-Means Clustering (Refresher).mp4
22.3 MB
23. Building a Boltzmann Machine/5. Building a Boltzmann Machine - Step 1.mp4
22.2 MB
23. Building a Boltzmann Machine/3. Building a Boltzmann Machine - Introduction.mp4
22.1 MB
23. Building a Boltzmann Machine/6. Building a Boltzmann Machine - Step 2.mp4
21.9 MB
15. Building a RNN/9. Building a RNN - Step 7.mp4
21.9 MB
10. Building a CNN/13. Building a CNN - Step 10.mp4
21.5 MB
1. Welcome to the course/4. Installing Python.mp4
21.4 MB
26. Building an AutoEncoder/6. Building an AutoEncoder - Step 3.mp4
21.1 MB
6. Evaluating, Improving and Tuning the ANN/2. Improving the ANN.mp4
20.8 MB
19. Building a SOM/3. Building a SOM - Step 2.mp4
20.4 MB
10. Building a CNN/4. Building a CNN - Step 1.mp4
20.1 MB
23. Building a Boltzmann Machine/10. Building a Boltzmann Machine - Step 6.mp4
19.7 MB
3. ANN Intuition/6. Gradient Descent.mp4
19.4 MB
18. SOMs Intuition/10. EXTRA K-means Clustering (part 3).mp4
19.4 MB
22. Boltzmann Machine Intuition/4. Editing Wikipedia - Our Contribution to the World.mp4
19.3 MB
23. Building a Boltzmann Machine/7. Building a Boltzmann Machine - Step 3.mp4
19.1 MB
4. Building an ANN/12. Building an ANN - Step 8.mp4
19.1 MB
4. Building an ANN/14. Building an ANN - Step 10.mp4
18.3 MB
4. Building an ANN/13. Building an ANN - Step 9.mp4
17.7 MB
3. ANN Intuition/7. Stochastic Gradient Descent.mp4
17.6 MB
23. Building a Boltzmann Machine/15. Building a Boltzmann Machine - Step 11.mp4
17.5 MB
4. Building an ANN/3. Business Problem Description.mp4
17.2 MB
18. SOMs Intuition/2. How do Self-Organizing Maps Work.mp4
16.7 MB
15. Building a RNN/5. Building a RNN - Step 3.mp4
16.7 MB
29. Data Preprocessing Template/2. Data Preprocessing - Step 2.mp4
16.6 MB
22. Boltzmann Machine Intuition/3. Energy-Based Models (EBM).mp4
16.5 MB
15. Building a RNN/4. Building a RNN - Step 2.mp4
16.4 MB
18. SOMs Intuition/6. How do Self-Organizing Maps Learn (Part 2).mp4
16.2 MB
23. Building a Boltzmann Machine/13. Building a Boltzmann Machine - Step 9.mp4
16.0 MB
3. ANN Intuition/3. The Activation Function.mp4
15.5 MB
9. CNN Intuition/5. Step 1(b) - ReLU Layer.mp4
14.8 MB
15. Building a RNN/3. Building a RNN - Step 1.mp4
14.4 MB
15. Building a RNN/14. Building a RNN - Step 12.mp4
14.1 MB
15. Building a RNN/10. Building a RNN - Step 8.mp4
14.1 MB
29. Data Preprocessing Template/1. Data Preprocessing - Step 1.mp4
13.9 MB
18. SOMs Intuition/7. Live SOM example.mp4
13.3 MB
10. Building a CNN/10. Building a CNN - Step 7.mp4
13.2 MB
18. SOMs Intuition/9. EXTRA K-means Clustering (part 2).mp4
12.9 MB
30. Classification Template/1. Logistic Regression Implementation - Step 1.mp4
12.8 MB
26. Building an AutoEncoder/9. Building an AutoEncoder - Step 5.mp4
12.4 MB
30. Classification Template/6. Classification Template.mp4
12.3 MB
25. AutoEncoders Intuition/6. Sparse Autoencoders.mp4
12.1 MB
15. Building a RNN/12. Building a RNN - Step 10.mp4
12.0 MB
26. Building an AutoEncoder/14. Building an AutoEncoder - Step 10.mp4
11.8 MB
25. AutoEncoders Intuition/4. Training an Auto Encoder.mp4
11.7 MB
23. Building a Boltzmann Machine/9. Building a Boltzmann Machine - Step 5.mp4
11.7 MB
3. ANN Intuition/8. Backpropagation.mp4
11.5 MB
22. Boltzmann Machine Intuition/7. Deep Belief Networks.mp4
10.8 MB
10. Building a CNN/8. Building a CNN - Step 5.mp4
10.4 MB
10. Building a CNN/9. Building a CNN - Step 6.mp4
10.2 MB
30. Classification Template/4. Logistic Regression Implementation - Step 4.mp4
10.1 MB
20. Mega Case Study/2. Mega Case Study - Step 2.mp4
10.1 MB
28. Regression & Classification Intuition/2. Simple Linear Regression Intuition - Step 1.mp4
9.9 MB
4. Building an ANN/11. Building an ANN - Step 7.mp4
9.4 MB
4. Building an ANN/7. Building an ANN - Step 3.mp4
8.8 MB
15. Building a RNN/11. Building a RNN - Step 9.mp4
8.6 MB
30. Classification Template/2. Logistic Regression Implementation - Step 2.mp4
8.5 MB
29. Data Preprocessing Template/7. Data Preprocessing Template.mp4
8.5 MB
9. CNN Intuition/9. Summary.mp4
8.3 MB
10. Building a CNN/3. Introduction to CNNs.mp4
8.2 MB
14. RNN Intuition/7. EXTRA LSTM Variations.mp4
7.7 MB
4. Building an ANN/10. Building an ANN - Step 6.mp4
7.4 MB
10. Building a CNN/11. Building a CNN - Step 8.mp4
7.1 MB
15. Building a RNN/8. Building a RNN - Step 6.mp4
7.1 MB
15. Building a RNN/1. How to get the dataset.mp4
6.8 MB
1. Welcome to the course/5. How to get the dataset.mp4
6.8 MB
10. Building a CNN/1. How to get the dataset.mp4
6.8 MB
19. Building a SOM/1. How to get the dataset.mp4
6.8 MB
23. Building a Boltzmann Machine/1. How to get the dataset.mp4
6.8 MB
26. Building an AutoEncoder/1. How to get the dataset.mp4
6.8 MB
4. Building an ANN/2. How to get the dataset.mp4
6.8 MB
25. AutoEncoders Intuition/5. Overcomplete hidden layers.mp4
6.7 MB
30. Classification Template/3. Logistic Regression Implementation - Step 3.mp4
6.2 MB
4. Building an ANN/8. Building an ANN - Step 4.mp4
6.2 MB
10. Building a CNN/5. Building a CNN - Step 2.mp4
6.1 MB
28. Regression & Classification Intuition/3. Simple Linear Regression Intuition - Step 2.mp4
5.6 MB
9. CNN Intuition/2. Plan of attack.mp4
5.1 MB
22. Boltzmann Machine Intuition/8. Deep Boltzmann Machines.mp4
5.1 MB
25. AutoEncoders Intuition/7. Denoising Autoencoders.mp4
5.0 MB
3. ANN Intuition/1. Plan of Attack.mp4
5.0 MB
18. SOMs Intuition/1. Plan of attack.mp4
4.7 MB
25. AutoEncoders Intuition/8. Contractive Autoencoders.mp4
4.6 MB
20. Mega Case Study/1. Mega Case Study - Step 1.mp4
4.5 MB
14. RNN Intuition/2. Plan of attack.mp4
4.4 MB
25. AutoEncoders Intuition/9. Stacked Autoencoders.mp4
3.8 MB
18. SOMs Intuition/3. Why revisit K-Means.mp4
3.6 MB
25. AutoEncoders Intuition/1. Plan of attack.mp4
3.5 MB
9. CNN Intuition/7. Step 3 - Flattening.mp4
3.4 MB
22. Boltzmann Machine Intuition/1. Plan of attack.mp4
3.4 MB
25. AutoEncoders Intuition/10. Deep Autoencoders.mp4
3.0 MB
10. Building a CNN/6. Building a CNN - Step 3.mp4
2.3 MB
25. AutoEncoders Intuition/3. A Note on Biases.mp4
2.2 MB
28. Regression & Classification Intuition/4. Multiple Linear Regression Intuition.mp4
1.9 MB
23. Building a Boltzmann Machine/8. Building a Boltzmann Machine - Step 4.srt
43.5 kB
26. Building an AutoEncoder/8. Building an AutoEncoder - Step 4.srt
42.1 kB
6. Evaluating, Improving and Tuning the ANN/1. Evaluating the ANN.srt
41.1 kB
10. Building a CNN/12. Building a CNN - Step 9.srt
40.6 kB
14. RNN Intuition/5. LSTMs.srt
40.3 kB
9. CNN Intuition/8. Step 4 - Full Connection.srt
39.5 kB
22. Boltzmann Machine Intuition/5. Restricted Boltzmann Machine.srt
38.7 kB
6. Evaluating, Improving and Tuning the ANN/3. Tuning the ANN.srt
37.5 kB
23. Building a Boltzmann Machine/17. Building a Boltzmann Machine - Step 13.srt
36.8 kB
4. Building an ANN/6. Building an ANN - Step 2.srt
36.8 kB
3. ANN Intuition/2. The Neuron.srt
36.6 kB
19. Building a SOM/4. Building a SOM - Step 3.srt
36.0 kB
30. Classification Template/5. Logistic Regression Implementation - Step 5.srt
35.8 kB
26. Building an AutoEncoder/10. Building an AutoEncoder - Step 6.srt
35.5 kB
9. CNN Intuition/10. Softmax & Cross-Entropy.srt
35.4 kB
23. Building a Boltzmann Machine/18. Building a Boltzmann Machine - Step 14.srt
35.0 kB
28. Regression & Classification Intuition/5. Logistic Regression Intuition.srt
33.4 kB
9. CNN Intuition/4. Step 1 - Convolution Operation.srt
33.0 kB
14. RNN Intuition/3. The idea behind Recurrent Neural Networks.srt
32.5 kB
26. Building an AutoEncoder/12. Building an AutoEncoder - Step 8.srt
31.9 kB
9. CNN Intuition/3. What are convolutional neural networks.srt
31.8 kB
22. Boltzmann Machine Intuition/6. Contrastive Divergence.srt
31.8 kB
15. Building a RNN/15. Building a RNN - Step 13.srt
31.7 kB
18. SOMs Intuition/4. K-Means Clustering (Refresher).srt
31.6 kB
11. Homework - What's that pet/2. Homework Solution.srt
31.5 kB
22. Boltzmann Machine Intuition/2. Boltzmann Machine.srt
31.0 kB
14. RNN Intuition/4. The Vanishing Gradient Problem.srt
30.4 kB
18. SOMs Intuition/5. How do Self-Organizing Maps Learn (Part 1).srt
29.8 kB
18. SOMs Intuition/8. Reading an Advanced SOM.srt
29.2 kB
9. CNN Intuition/6. Step 2 - Pooling.srt
29.2 kB
14. RNN Intuition/6. Practical intuition.srt
28.6 kB
20. Mega Case Study/3. Mega Case Study - Step 3.srt
28.4 kB
26. Building an AutoEncoder/11. Building an AutoEncoder - Step 7.srt
28.3 kB
3. ANN Intuition/5. How do Neural Networks learn.srt
28.1 kB
26. Building an AutoEncoder/13. Building an AutoEncoder - Step 9.srt
27.8 kB
10. Building a CNN/7. Building a CNN - Step 4.srt
27.3 kB
4. Building an ANN/5. Building an ANN - Step 1.srt
27.2 kB
3. ANN Intuition/4. How do Neural Networks work.srt
26.9 kB
19. Building a SOM/2. Building a SOM - Step 1.srt
26.9 kB
15. Building a RNN/6. Building a RNN - Step 4.srt
26.0 kB
18. SOMs Intuition/10. EXTRA K-means Clustering (part 3).srt
25.6 kB
4. Building an ANN/9. Building an ANN - Step 5.srt
25.5 kB
23. Building a Boltzmann Machine/12. Building a Boltzmann Machine - Step 8.srt
25.3 kB
23. Building a Boltzmann Machine/16. Building a Boltzmann Machine - Step 12.srt
25.2 kB
29. Data Preprocessing Template/4. Data Preprocessing - Step 4.srt
24.6 kB
26. Building an AutoEncoder/5. Building an AutoEncoder - Step 2.srt
24.6 kB
26. Building an AutoEncoder/15. Building an AutoEncoder - Step 11.srt
24.5 kB
1. Welcome to the course/2. What is Deep Learning.srt
24.4 kB
26. Building an AutoEncoder/4. Building an AutoEncoder - Step 1.srt
23.6 kB
23. Building a Boltzmann Machine/14. Building a Boltzmann Machine - Step 10.srt
23.1 kB
22. Boltzmann Machine Intuition/3. Energy-Based Models (EBM).srt
22.4 kB
25. AutoEncoders Intuition/2. Auto Encoders.srt
21.9 kB
19. Building a SOM/5. Building a SOM - Step 4.srt
21.9 kB
20. Mega Case Study/4. Mega Case Study - Step 4.srt
21.9 kB
29. Data Preprocessing Template/6. Data Preprocessing - Step 6.srt
21.9 kB
29. Data Preprocessing Template/5. Data Preprocessing - Step 5.srt
21.7 kB
5. Homework Challenge - Should we say goodbye to that customer/2. Homework Solution.srt
21.7 kB
23. Building a Boltzmann Machine/11. Building a Boltzmann Machine - Step 7.srt
21.3 kB
23. Building a Boltzmann Machine/3. Building a Boltzmann Machine - Introduction.srt
21.0 kB
15. Building a RNN/7. Building a RNN - Step 5.srt
20.1 kB
29. Data Preprocessing Template/3. Data Preprocessing - Step 3.srt
19.9 kB
19. Building a SOM/3. Building a SOM - Step 2.srt
19.7 kB
3. ANN Intuition/6. Gradient Descent.srt
19.6 kB
15. Building a RNN/13. Building a RNN - Step 11.srt
19.1 kB
10. Building a CNN/4. Building a CNN - Step 1.srt
19.0 kB
23. Building a Boltzmann Machine/5. Building a Boltzmann Machine - Step 1.srt
18.9 kB
23. Building a Boltzmann Machine/6. Building a Boltzmann Machine - Step 2.srt
18.8 kB
18. SOMs Intuition/6. How do Self-Organizing Maps Learn (Part 2).srt
18.8 kB
18. SOMs Intuition/2. How do Self-Organizing Maps Work.srt
18.7 kB
15. Building a RNN/17. Building a RNN - Step 15.srt
18.1 kB
3. ANN Intuition/7. Stochastic Gradient Descent.srt
18.0 kB
10. Building a CNN/13. Building a CNN - Step 10.srt
17.7 kB
18. SOMs Intuition/9. EXTRA K-means Clustering (part 2).srt
17.5 kB
3. ANN Intuition/3. The Activation Function.srt
17.3 kB
23. Building a Boltzmann Machine/7. Building a Boltzmann Machine - Step 3.srt
16.8 kB
1. Welcome to the course/4. Installing Python.srt
16.7 kB
26. Building an AutoEncoder/6. Building an AutoEncoder - Step 3.srt
16.6 kB
23. Building a Boltzmann Machine/10. Building a Boltzmann Machine - Step 6.srt
16.4 kB
15. Building a RNN/9. Building a RNN - Step 7.srt
16.3 kB
29. Data Preprocessing Template/1. Data Preprocessing - Step 1.srt
15.7 kB
4. Building an ANN/12. Building an ANN - Step 8.srt
15.6 kB
29. Data Preprocessing Template/2. Data Preprocessing - Step 2.srt
15.5 kB
15. Building a RNN/16. Building a RNN - Step 14.srt
14.5 kB
4. Building an ANN/14. Building an ANN - Step 10.srt
14.4 kB
6. Evaluating, Improving and Tuning the ANN/2. Improving the ANN.srt
14.0 kB
23. Building a Boltzmann Machine/13. Building a Boltzmann Machine - Step 9.srt
13.9 kB
25. AutoEncoders Intuition/4. Training an Auto Encoder.srt
13.7 kB
23. Building a Boltzmann Machine/15. Building a Boltzmann Machine - Step 11.srt
13.1 kB
15. Building a RNN/4. Building a RNN - Step 2.srt
13.0 kB
9. CNN Intuition/5. Step 1(b) - ReLU Layer.srt
12.8 kB
10. Building a CNN/10. Building a CNN - Step 7.srt
12.7 kB
25. AutoEncoders Intuition/6. Sparse Autoencoders.srt
12.5 kB
15. Building a RNN/3. Building a RNN - Step 1.srt
12.3 kB
4. Building an ANN/13. Building an ANN - Step 9.srt
12.0 kB
15. Building a RNN/10. Building a RNN - Step 8.srt
11.7 kB
28. Regression & Classification Intuition/2. Simple Linear Regression Intuition - Step 1.srt
11.5 kB
22. Boltzmann Machine Intuition/7. Deep Belief Networks.srt
10.8 kB
15. Building a RNN/5. Building a RNN - Step 3.srt
10.7 kB
23. Building a Boltzmann Machine/9. Building a Boltzmann Machine - Step 5.srt
10.6 kB
10. Building a CNN/9. Building a CNN - Step 6.srt
10.6 kB
4. Building an ANN/3. Business Problem Description.srt
10.6 kB
3. ANN Intuition/8. Backpropagation.srt
10.2 kB
26. Building an AutoEncoder/9. Building an AutoEncoder - Step 5.srt
10.2 kB
10. Building a CNN/8. Building a CNN - Step 5.srt
10.1 kB
30. Classification Template/1. Logistic Regression Implementation - Step 1.srt
10.0 kB
15. Building a RNN/14. Building a RNN - Step 12.srt
9.7 kB
15. Building a RNN/12. Building a RNN - Step 10.srt
9.6 kB
26. Building an AutoEncoder/14. Building an AutoEncoder - Step 10.srt
9.5 kB
18. SOMs Intuition/7. Live SOM example.srt
9.4 kB
20. Mega Case Study/2. Mega Case Study - Step 2.srt
9.0 kB
10. Building a CNN/3. Introduction to CNNs.srt
8.8 kB
9. CNN Intuition/9. Summary.srt
8.7 kB
30. Classification Template/6. Classification Template.srt
8.4 kB
30. Classification Template/4. Logistic Regression Implementation - Step 4.srt
8.3 kB
25. AutoEncoders Intuition/5. Overcomplete hidden layers.srt
8.3 kB
4. Building an ANN/11. Building an ANN - Step 7.srt
8.1 kB
29. Data Preprocessing Template/7. Data Preprocessing Template.srt
8.1 kB
9. CNN Intuition/2. Plan of attack.srt
7.6 kB
14. RNN Intuition/7. EXTRA LSTM Variations.srt
6.9 kB
20. Mega Case Study/1. Mega Case Study - Step 1.srt
6.8 kB
22. Boltzmann Machine Intuition/4. Editing Wikipedia - Our Contribution to the World.srt
6.8 kB
18. SOMs Intuition/1. Plan of attack.srt
6.8 kB
15. Building a RNN/11. Building a RNN - Step 9.srt
6.7 kB
4. Building an ANN/7. Building an ANN - Step 3.srt
6.7 kB
22. Boltzmann Machine Intuition/8. Deep Boltzmann Machines.srt
6.4 kB
1. Welcome to the course/1. Updates on Udemy Reviews.srt
6.4 kB
15. Building a RNN/8. Building a RNN - Step 6.srt
6.3 kB
30. Classification Template/2. Logistic Regression Implementation - Step 2.srt
6.2 kB
4. Building an ANN/10. Building an ANN - Step 6.srt
6.2 kB
28. Regression & Classification Intuition/3. Simple Linear Regression Intuition - Step 2.srt
6.2 kB
10. Building a CNN/5. Building a CNN - Step 2.srt
5.8 kB
10. Building a CNN/11. Building a CNN - Step 8.srt
5.8 kB
3. ANN Intuition/1. Plan of Attack.srt
5.7 kB
25. AutoEncoders Intuition/7. Denoising Autoencoders.srt
5.4 kB
22. Boltzmann Machine Intuition/1. Plan of attack.srt
5.3 kB
30. Classification Template/3. Logistic Regression Implementation - Step 3.srt
5.1 kB
25. AutoEncoders Intuition/8. Contractive Autoencoders.srt
5.0 kB
14. RNN Intuition/2. Plan of attack.srt
5.0 kB
18. SOMs Intuition/3. Why revisit K-Means.srt
4.9 kB
25. AutoEncoders Intuition/1. Plan of attack.srt
4.8 kB
4. Building an ANN/8. Building an ANN - Step 4.srt
4.6 kB
23. Building a Boltzmann Machine/19. Evaluating the Boltzmann Machine.html
4.6 kB
25. AutoEncoders Intuition/10. Deep Autoencoders.srt
3.9 kB
9. CNN Intuition/7. Step 3 - Flattening.srt
3.9 kB
1. Welcome to the course/5. How to get the dataset.srt
3.6 kB
10. Building a CNN/1. How to get the dataset.srt
3.6 kB
15. Building a RNN/1. How to get the dataset.srt
3.6 kB
19. Building a SOM/1. How to get the dataset.srt
3.6 kB
23. Building a Boltzmann Machine/1. How to get the dataset.srt
3.6 kB
26. Building an AutoEncoder/1. How to get the dataset.srt
3.6 kB
4. Building an ANN/2. How to get the dataset.srt
3.6 kB
25. AutoEncoders Intuition/9. Stacked Autoencoders.srt
3.4 kB
31. Bonus Lectures/1. YOUR SPECIAL BONUS.html
3.1 kB
25. AutoEncoders Intuition/3. A Note on Biases.srt
2.8 kB
26. Building an AutoEncoder/16. THANK YOU bonus video.srt
2.5 kB
1. Welcome to the course/3. BONUS Learning Paths.html
2.4 kB
10. Building a CNN/6. Building a CNN - Step 3.srt
2.4 kB
28. Regression & Classification Intuition/4. Multiple Linear Regression Intuition.srt
2.2 kB
1. Welcome to the course/8. FAQBot!.html
1.8 kB
16. Evaluating, Improving and Tuning the RNN/1. Evaluating the RNN.html
1.8 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
1.6 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
1.4 kB
16. Evaluating, Improving and Tuning the RNN/2. Improving the RNN.html
1.3 kB
1. Welcome to the course/6. BONUS Meet Your Instructors.html
1.2 kB
13. ---------------------- Part 3 - Recurrent Neural Networks ----------------------/1. Welcome to Part 3 - Recurrent Neural Networks.html
1.1 kB
24. ---------------------------- Part 6 - AutoEncoders ----------------------------/1. Welcome to Part 6 - AutoEncoders.html
1.1 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
28. Regression & Classification Intuition/1. What You Need for Regression & Classification.html
648 Bytes
1. Welcome to the course/7. 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
[DesireCourse.Net].url
51 Bytes
[CourseClub.Me].url
48 Bytes
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