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种子名称： [DesireCourse.Net] Udemy - Deep Learning A-Z™ Hands-On Artificial Neural Networks
文件类型： 视频
文件数目： 155个文件
文件大小： 3.06 GB
收录时间： 2020-10-15 14:26
已经下载： 3次
资源热度： 377
最近下载： 2024-12-16 02:28

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[DesireCourse.Net] Udemy - Deep Learning A-Z™ Hands-On Artificial Neural Networks.torrent

1. Welcome to the course/1. Updates on Udemy Reviews.mp461.15MB

1. Welcome to the course/2. What is Deep Learning.mp431.31MB

1. Welcome to the course/4. Installing Python.mp420.38MB

1. Welcome to the course/5. How to get the dataset.mp46.49MB

10. Building a CNN/1. How to get the dataset.mp46.49MB

10. Building a CNN/10. Building a CNN - Step 7.mp412.58MB

10. Building a CNN/11. Building a CNN - Step 8.mp46.8MB

10. Building a CNN/12. Building a CNN - Step 9.mp446.87MB

10. Building a CNN/13. Building a CNN - Step 10.mp420.54MB

10. Building a CNN/3. Introduction to CNNs.mp47.85MB

10. Building a CNN/4. Building a CNN - Step 1.mp419.18MB

10. Building a CNN/5. Building a CNN - Step 2.mp45.86MB

10. Building a CNN/6. Building a CNN - Step 3.mp42.23MB

10. Building a CNN/7. Building a CNN - Step 4.mp427.2MB

10. Building a CNN/8. Building a CNN - Step 5.mp49.91MB

10. Building a CNN/9. Building a CNN - Step 6.mp49.7MB

11. Homework - What's that pet/2. Homework Solution.mp440.97MB

14. RNN Intuition/2. Plan of attack.mp44.19MB

14. RNN Intuition/3. The idea behind Recurrent Neural Networks.mp437.3MB

14. RNN Intuition/4. The Vanishing Gradient Problem.mp429.01MB

14. RNN Intuition/5. LSTMs.mp445.97MB

14. RNN Intuition/6. Practical intuition.mp452.84MB

14. RNN Intuition/7. EXTRA LSTM Variations.mp47.33MB

15. Building a RNN/1. How to get the dataset.mp46.5MB

15. Building a RNN/10. Building a RNN - Step 8.mp413.43MB

15. Building a RNN/11. Building a RNN - Step 9.mp48.18MB

15. Building a RNN/12. Building a RNN - Step 10.mp411.43MB

15. Building a RNN/13. Building a RNN - Step 11.mp429.29MB

15. Building a RNN/14. Building a RNN - Step 12.mp413.47MB

15. Building a RNN/15. Building a RNN - Step 13.mp439.86MB

15. Building a RNN/16. Building a RNN - Step 14.mp421.54MB

15. Building a RNN/17. Building a RNN - Step 15.mp421.67MB

15. Building a RNN/3. Building a RNN - Step 1.mp413.7MB

15. Building a RNN/4. Building a RNN - Step 2.mp415.6MB

15. Building a RNN/5. Building a RNN - Step 3.mp415.91MB

15. Building a RNN/6. Building a RNN - Step 4.mp437.11MB

15. Building a RNN/7. Building a RNN - Step 5.mp426.22MB

15. Building a RNN/8. Building a RNN - Step 6.mp46.77MB

15. Building a RNN/9. Building a RNN - Step 7.mp420.84MB

18. SOMs Intuition/1. Plan of attack.mp44.45MB

18. SOMs Intuition/10. EXTRA K-means Clustering (part 3).mp418.49MB

18. SOMs Intuition/2. How do Self-Organizing Maps Work.mp415.96MB

18. SOMs Intuition/3. Why revisit K-Means.mp43.45MB

18. SOMs Intuition/4. K-Means Clustering (Refresher).mp421.23MB

18. SOMs Intuition/5. How do Self-Organizing Maps Learn (Part 1).mp425.08MB

18. SOMs Intuition/6. How do Self-Organizing Maps Learn (Part 2).mp415.49MB

18. SOMs Intuition/7. Live SOM example.mp412.69MB

18. SOMs Intuition/8. Reading an Advanced SOM.mp443.18MB

18. SOMs Intuition/9. EXTRA K-means Clustering (part 2).mp412.34MB

19. Building a SOM/1. How to get the dataset.mp46.49MB

19. Building a SOM/2. Building a SOM - Step 1.mp430.67MB

19. Building a SOM/3. Building a SOM - Step 2.mp419.43MB

19. Building a SOM/4. Building a SOM - Step 3.mp436.03MB

19. Building a SOM/5. Building a SOM - Step 4.mp428.73MB

20. Mega Case Study/1. Mega Case Study - Step 1.mp44.28MB

20. Mega Case Study/2. Mega Case Study - Step 2.mp49.68MB

20. Mega Case Study/3. Mega Case Study - Step 3.mp435.2MB

20. Mega Case Study/4. Mega Case Study - Step 4.mp422.74MB

22. Boltzmann Machine Intuition/1. Plan of attack.mp43.26MB

22. Boltzmann Machine Intuition/2. Boltzmann Machine.mp425.01MB

22. Boltzmann Machine Intuition/3. Energy-Based Models (EBM).mp415.72MB

22. Boltzmann Machine Intuition/4. Editing Wikipedia - Our Contribution to the World.mp418.43MB

22. Boltzmann Machine Intuition/5. Restricted Boltzmann Machine.mp431.89MB

22. Boltzmann Machine Intuition/6. Contrastive Divergence.mp424.91MB

22. Boltzmann Machine Intuition/7. Deep Belief Networks.mp410.34MB

22. Boltzmann Machine Intuition/8. Deep Boltzmann Machines.mp44.86MB

23. Building a Boltzmann Machine/1. How to get the dataset.mp46.49MB

23. Building a Boltzmann Machine/10. Building a Boltzmann Machine - Step 6.mp418.8MB

23. Building a Boltzmann Machine/11. Building a Boltzmann Machine - Step 7.mp422.9MB

23. Building a Boltzmann Machine/12. Building a Boltzmann Machine - Step 8.mp429.2MB

23. Building a Boltzmann Machine/13. Building a Boltzmann Machine - Step 9.mp415.27MB

23. Building a Boltzmann Machine/14. Building a Boltzmann Machine - Step 10.mp424.42MB

23. Building a Boltzmann Machine/15. Building a Boltzmann Machine - Step 11.mp416.68MB

23. Building a Boltzmann Machine/16. Building a Boltzmann Machine - Step 12.mp430.95MB

23. Building a Boltzmann Machine/17. Building a Boltzmann Machine - Step 13.mp442.97MB

23. Building a Boltzmann Machine/18. Building a Boltzmann Machine - Step 14.mp440.43MB

23. Building a Boltzmann Machine/3. Building a Boltzmann Machine - Introduction.mp421.06MB

23. Building a Boltzmann Machine/5. Building a Boltzmann Machine - Step 1.mp421.16MB

23. Building a Boltzmann Machine/6. Building a Boltzmann Machine - Step 2.mp420.85MB

23. Building a Boltzmann Machine/7. Building a Boltzmann Machine - Step 3.mp418.21MB

23. Building a Boltzmann Machine/8. Building a Boltzmann Machine - Step 4.mp445.64MB

23. Building a Boltzmann Machine/9. Building a Boltzmann Machine - Step 5.mp411.12MB

25. AutoEncoders Intuition/1. Plan of attack.mp43.36MB

25. AutoEncoders Intuition/10. Deep Autoencoders.mp42.85MB

25. AutoEncoders Intuition/2. Auto Encoders.mp421.54MB

25. AutoEncoders Intuition/3. A Note on Biases.mp42.05MB

25. AutoEncoders Intuition/4. Training an Auto Encoder.mp411.13MB

25. AutoEncoders Intuition/5. Overcomplete hidden layers.mp46.42MB

25. AutoEncoders Intuition/6. Sparse Autoencoders.mp411.52MB

25. AutoEncoders Intuition/7. Denoising Autoencoders.mp44.75MB

25. AutoEncoders Intuition/8. Contractive Autoencoders.mp44.35MB

25. AutoEncoders Intuition/9. Stacked Autoencoders.mp43.63MB

26. Building an AutoEncoder/1. How to get the dataset.mp46.49MB

26. Building an AutoEncoder/10. Building an AutoEncoder - Step 6.mp437.92MB

26. Building an AutoEncoder/11. Building an AutoEncoder - Step 7.mp433.7MB

26. Building an AutoEncoder/12. Building an AutoEncoder - Step 8.mp433.83MB

26. Building an AutoEncoder/13. Building an AutoEncoder - Step 9.mp431.61MB

26. Building an AutoEncoder/14. Building an AutoEncoder - Step 10.mp411.26MB

26. Building an AutoEncoder/15. Building an AutoEncoder - Step 11.mp428.29MB

26. Building an AutoEncoder/16. THANK YOU bonus video.mp452.3MB

26. Building an AutoEncoder/4. Building an AutoEncoder - Step 1.mp426.04MB

26. Building an AutoEncoder/5. Building an AutoEncoder - Step 2.mp427.81MB

26. Building an AutoEncoder/6. Building an AutoEncoder - Step 3.mp420.09MB

26. Building an AutoEncoder/8. Building an AutoEncoder - Step 4.mp449.56MB

26. Building an AutoEncoder/9. Building an AutoEncoder - Step 5.mp411.87MB

28. Regression & Classification Intuition/2. Simple Linear Regression Intuition - Step 1.mp49.47MB

28. Regression & Classification Intuition/3. Simple Linear Regression Intuition - Step 2.mp45.37MB

28. Regression & Classification Intuition/4. Multiple Linear Regression Intuition.mp41.82MB

28. Regression & Classification Intuition/5. Logistic Regression Intuition.mp429.17MB

29. Data Preprocessing Template/1. Data Preprocessing - Step 1.mp413.25MB

29. Data Preprocessing Template/2. Data Preprocessing - Step 2.mp415.86MB

29. Data Preprocessing Template/3. Data Preprocessing - Step 3.mp421.74MB

29. Data Preprocessing Template/4. Data Preprocessing - Step 4.mp428.95MB

29. Data Preprocessing Template/5. Data Preprocessing - Step 5.mp422.89MB

29. Data Preprocessing Template/6. Data Preprocessing - Step 6.mp422.81MB

29. Data Preprocessing Template/7. Data Preprocessing Template.mp48.13MB

3. ANN Intuition/1. Plan of Attack.mp44.74MB

3. ANN Intuition/2. The Neuron.mp429.57MB

3. ANN Intuition/3. The Activation Function.mp414.76MB

3. ANN Intuition/4. How do Neural Networks work.mp423.54MB

3. ANN Intuition/5. How do Neural Networks learn.mp426.55MB

3. ANN Intuition/6. Gradient Descent.mp418.53MB

3. ANN Intuition/7. Stochastic Gradient Descent.mp416.83MB

3. ANN Intuition/8. Backpropagation.mp410.93MB

30. Classification Template/1. Logistic Regression Implementation - Step 1.mp412.2MB

30. Classification Template/2. Logistic Regression Implementation - Step 2.mp48.14MB

30. Classification Template/3. Logistic Regression Implementation - Step 3.mp45.96MB

30. Classification Template/4. Logistic Regression Implementation - Step 4.mp49.68MB

30. Classification Template/5. Logistic Regression Implementation - Step 5.mp442.48MB

30. Classification Template/6. Classification Template.mp411.72MB

4. Building an ANN/10. Building an ANN - Step 6.mp47.05MB

4. Building an ANN/11. Building an ANN - Step 7.mp48.99MB

4. Building an ANN/12. Building an ANN - Step 8.mp418.18MB

4. Building an ANN/13. Building an ANN - Step 9.mp416.9MB

4. Building an ANN/14. Building an ANN - Step 10.mp417.44MB

4. Building an ANN/2. How to get the dataset.mp46.49MB

4. Building an ANN/3. Business Problem Description.mp416.37MB

4. Building an ANN/5. Building an ANN - Step 1.mp424.29MB

4. Building an ANN/6. Building an ANN - Step 2.mp445.86MB

4. Building an ANN/7. Building an ANN - Step 3.mp48.37MB

4. Building an ANN/8. Building an ANN - Step 4.mp45.95MB

4. Building an ANN/9. Building an ANN - Step 5.mp429.58MB

5. Homework Challenge - Should we say goodbye to that customer/2. Homework Solution.mp437.62MB

6. Evaluating, Improving and Tuning the ANN/1. Evaluating the ANN.mp455.84MB

6. Evaluating, Improving and Tuning the ANN/2. Improving the ANN.mp419.83MB

6. Evaluating, Improving and Tuning the ANN/3. Tuning the ANN.mp450.76MB

9. CNN Intuition/10. Softmax & Cross-Entropy.mp433.24MB

9. CNN Intuition/2. Plan of attack.mp44.91MB

9. CNN Intuition/3. What are convolutional neural networks.mp429.5MB

9. CNN Intuition/4. Step 1 - Convolution Operation.mp431.02MB

9. CNN Intuition/5. Step 1(b) - ReLU Layer.mp414.09MB

9. CNN Intuition/6. Step 2 - Pooling.mp440.25MB

9. CNN Intuition/7. Step 3 - Flattening.mp43.27MB

9. CNN Intuition/8. Step 4 - Full Connection.mp442.74MB

9. CNN Intuition/9. Summary.mp47.92MB