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

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

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收录时间：2021-04-04
最近下载：2024-12-07

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文件列表

  • 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
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  • 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
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  • 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
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  • 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
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  • 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
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  • 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
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  • 4. Building an ANN/4. Installing Keras.html 1.4 kB
  • 26. Building an AutoEncoder/2. Installing PyTorch.html 1.4 kB
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  • 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
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  • 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
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  • 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
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  • 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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