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| [CourseClub.NET].url |
123б |
| [FCS Forum].url |
133б |
| [FreeCourseSite.com].url |
127б |
| 1. (Legacy) Restricted Boltzmann Machine Theory.mp4 |
14.39Мб |
| 1. (Legacy) Restricted Boltzmann Machine Theory.vtt |
10.39Кб |
| 1. (Review) Theano Basics.mp4 |
93.43Мб |
| 1. (Review) Theano Basics.vtt |
6.31Кб |
| 1. Application of PCA and SVD to NLP (Natural Language Processing).mp4 |
3.93Мб |
| 1. Application of PCA and SVD to NLP (Natural Language Processing).vtt |
351б |
| 1. Autoencoders.mp4 |
5.82Мб |
| 1. Autoencoders.vtt |
3.94Кб |
| 1. Basic Outline for RBMs.mp4 |
32.98Мб |
| 1. Basic Outline for RBMs.vtt |
5.64Кб |
| 1. Exercises on feature visualization and interpretation.mp4 |
3.75Мб |
| 1. Exercises on feature visualization and interpretation.vtt |
351б |
| 1. Introduction and Outline.mp4 |
3.27Мб |
| 1. Introduction and Outline.vtt |
351б |
| 1. Recommender Systems Section Introduction.mp4 |
68.17Мб |
| 1. Recommender Systems Section Introduction.vtt |
351б |
| 1. The Vanishing Gradient Problem Description.mp4 |
5.20Мб |
| 1. The Vanishing Gradient Problem Description.vtt |
351б |
| 1. t-SNE Theory.mp4 |
7.90Мб |
| 1. t-SNE Theory.vtt |
4.78Кб |
| 1. What does PCA do.mp4 |
27.79Мб |
| 1. What does PCA do.vtt |
4.96Кб |
| 1. What is the Appendix.mp4 |
5.45Мб |
| 1. What is the Appendix.vtt |
3.28Кб |
| 10. Deep Autoencoder Visualization Description.mp4 |
2.46Мб |
| 10. Deep Autoencoder Visualization Description.vtt |
2.00Кб |
| 10. Python 2 vs Python 3.mp4 |
7.84Мб |
| 10. Python 2 vs Python 3.vtt |
5.35Кб |
| 10. RBM in Code (Theano) with Greedy Layer-Wise Training on MNIST.mp4 |
47.76Мб |
| 10. RBM in Code (Theano) with Greedy Layer-Wise Training on MNIST.vtt |
6.77Кб |
| 10. Recommender RBM Code Speedup.mp4 |
82.95Мб |
| 10. Recommender RBM Code Speedup.vtt |
82.96Мб |
| 10. SVD (Singular Value Decomposition).mp4 |
42.47Мб |
| 10. SVD (Singular Value Decomposition).vtt |
10.33Кб |
| 11. Deep Autoencoder Visualization in Code.mp4 |
27.85Мб |
| 11. Deep Autoencoder Visualization in Code.vtt |
6.67Кб |
| 11. Is Theano Dead.mp4 |
17.82Мб |
| 11. Is Theano Dead.vtt |
11.30Кб |
| 11. RBM in Code (Tensorflow).mp4 |
13.70Мб |
| 11. RBM in Code (Tensorflow).vtt |
351б |
| 12. An Autoencoder in 1 Line of Code.mp4 |
24.94Мб |
| 12. An Autoencoder in 1 Line of Code.vtt |
5.08Кб |
| 12. What order should I take your courses in (part 1).mp4 |
29.33Мб |
| 12. What order should I take your courses in (part 1).vtt |
14.09Кб |
| 13. What order should I take your courses in (part 2).mp4 |
37.62Мб |
| 13. What order should I take your courses in (part 2).vtt |
20.24Кб |
| 2. (Legacy) Deriving Conditional Probabilities from Joint Probability.mp4 |
9.37Мб |
| 2. (Legacy) Deriving Conditional Probabilities from Joint Probability.vtt |
5.72Кб |
| 2. (Review) Theano Neural Network in Code.mp4 |
87.03Мб |
| 2. (Review) Theano Neural Network in Code.vtt |
3.29Кб |
| 2. BONUS Where to get Udemy coupons and FREE deep learning material.mp4 |
4.03Мб |
| 2. BONUS Where to get Udemy coupons and FREE deep learning material.vtt |
2.99Кб |
| 2. Denoising Autoencoders.mp4 |
3.44Мб |
| 2. Denoising Autoencoders.vtt |
2.26Кб |
| 2. How does PCA work.mp4 |
50.93Мб |
| 2. How does PCA work.vtt |
12.37Кб |
| 2. Introduction to RBMs.mp4 |
39.44Мб |
| 2. Introduction to RBMs.vtt |
351б |
| 2. Latent Semantic Analysis in Code.mp4 |
25.62Мб |
| 2. Latent Semantic Analysis in Code.vtt |
351б |
| 2. The Vanishing Gradient Problem Demo in Code.mp4 |
31.29Мб |
| 2. The Vanishing Gradient Problem Demo in Code.vtt |
351б |
| 2. t-SNE Visualization.mp4 |
13.03Мб |
| 2. t-SNE Visualization.vtt |
4.82Кб |
| 2. Where does this course fit into your deep learning studies.mp4 |
5.19Мб |
| 2. Where does this course fit into your deep learning studies.vtt |
351б |
| 2. Why Autoencoders and RBMs work.mp4 |
38.19Мб |
| 2. Why Autoencoders and RBMs work.vtt |
351б |
| 3. (Legacy) Contrastive Divergence for RBM Training.mp4 |
4.85Мб |
| 3. (Legacy) Contrastive Divergence for RBM Training.vtt |
3.01Кб |
| 3. (Review) Tensorflow Basics.mp4 |
81.47Мб |
| 3. (Review) Tensorflow Basics.vtt |
5.06Кб |
| 3. Application of t-SNE + K-Means Finding Clusters of Related Words.mp4 |
25.99Мб |
| 3. Application of t-SNE + K-Means Finding Clusters of Related Words.vtt |
351б |
| 3. Data Preparation and Logistics.mp4 |
21.21Мб |
| 3. Data Preparation and Logistics.vtt |
351б |
| 3. How to Succeed in this Course.mp4 |
6.41Мб |
| 3. How to Succeed in this Course.vtt |
351б |
| 3. Motivation Behind RBMs.mp4 |
34.00Мб |
| 3. Motivation Behind RBMs.vtt |
351б |
| 3. Stacked Autoencoders.mp4 |
6.60Мб |
| 3. Stacked Autoencoders.vtt |
4.24Кб |
| 3. t-SNE on the Donut.mp4 |
15.10Мб |
| 3. t-SNE on the Donut.vtt |
2.23Кб |
| 3. Why does PCA work (PCA derivation).mp4 |
51.32Мб |
| 3. Why does PCA work (PCA derivation).vtt |
351б |
| 3. Windows-Focused Environment Setup 2018.mp4 |
186.39Мб |
| 3. Windows-Focused Environment Setup 2018.vtt |
17.39Кб |
| 4. (Legacy) How to derive the free energy formula.mp4 |
10.88Мб |
| 4. (Legacy) How to derive the free energy formula.vtt |
5.60Кб |
| 4. (Review) Tensorflow Neural Network in Code.mp4 |
97.39Мб |
| 4. (Review) Tensorflow Neural Network in Code.vtt |
4.78Кб |
| 4. AutoRec.mp4 |
48.90Мб |
| 4. AutoRec.vtt |
351б |
| 4. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 |
43.92Мб |
| 4. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.vtt |
12.40Кб |
| 4. Intractability.mp4 |
12.92Мб |
| 4. Intractability.vtt |
351б |
| 4. PCA only rotates.mp4 |
16.45Мб |
| 4. PCA only rotates.vtt |
351б |
| 4. t-SNE on XOR.mp4 |
9.31Мб |
| 4. t-SNE on XOR.vtt |
3.64Кб |
| 4. Where to get the code and data.mp4 |
26.43Мб |
| 4. Where to get the code and data.vtt |
351б |
| 4. Writing the autoencoder class in code (Theano).mp4 |
38.52Мб |
| 4. Writing the autoencoder class in code (Theano).vtt |
6.08Кб |
| 5. (Review) Keras Basics.mp4 |
27.64Мб |
| 5. (Review) Keras Basics.vtt |
8.05Кб |
| 5. AutoRec in Code.mp4 |
102.28Мб |
| 5. AutoRec in Code.vtt |
12.62Кб |
| 5. How to Code by Yourself (part 1).mp4 |
24.53Мб |
| 5. How to Code by Yourself (part 1).vtt |
19.78Кб |
| 5. MNIST visualization, finding the optimal number of principal components.mp4 |
9.39Мб |
| 5. MNIST visualization, finding the optimal number of principal components.vtt |
3.33Кб |
| 5. Neural Network Equations.mp4 |
31.71Мб |
| 5. Neural Network Equations.vtt |
7.42Кб |
| 5. Tensorflow or Theano - Your Choice!.mp4 |
18.93Мб |
| 5. Tensorflow or Theano - Your Choice!.vtt |
351б |
| 5. Testing our Autoencoder (Theano).mp4 |
11.36Мб |
| 5. Testing our Autoencoder (Theano).vtt |
2.67Кб |
| 5. t-SNE on MNIST.mp4 |
4.35Мб |
| 5. t-SNE on MNIST.vtt |
1.59Кб |
| 6. (Review) Keras in Code pt 1.mp4 |
66.17Мб |
| 6. (Review) Keras in Code pt 1.vtt |
6.47Кб |
| 6. Categorical RBM for Recommender System Ratings.mp4 |
47.59Мб |
| 6. Categorical RBM for Recommender System Ratings.vtt |
12.05Кб |
| 6. How to Code by Yourself (part 2).mp4 |
14.80Мб |
| 6. How to Code by Yourself (part 2).vtt |
11.62Кб |
| 6. PCA implementation.mp4 |
32.09Мб |
| 6. PCA implementation.vtt |
351б |
| 6. Training an RBM (part 1).mp4 |
49.08Мб |
| 6. Training an RBM (part 1).vtt |
11.76Кб |
| 6. What are the practical applications of unsupervised deep learning.mp4 |
11.66Мб |
| 6. What are the practical applications of unsupervised deep learning.vtt |
351б |
| 6. Writing the deep neural network class in code (Theano).mp4 |
41.97Мб |
| 6. Writing the deep neural network class in code (Theano).vtt |
6.37Кб |
| 7. (Review) Keras in Code pt 2.mp4 |
38.67Мб |
| 7. (Review) Keras in Code pt 2.vtt |
4.70Кб |
| 7. Autoencoder in Code (Tensorflow).mp4 |
24.45Мб |
| 7. Autoencoder in Code (Tensorflow).vtt |
8.17Кб |
| 7. How to Succeed in this Course (Long Version).mp4 |
18.31Мб |
| 7. How to Succeed in this Course (Long Version).vtt |
12.79Кб |
| 7. PCA for NLP.mp4 |
16.62Мб |
| 7. PCA for NLP.vtt |
3.89Кб |
| 7. Recommender RBM Code pt 1.mp4 |
70.42Мб |
| 7. Recommender RBM Code pt 1.vtt |
8.74Кб |
| 7. Training an RBM (part 2).mp4 |
27.34Мб |
| 7. Training an RBM (part 2).vtt |
6.44Кб |
| 8. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 |
38.95Мб |
| 8. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.vtt |
27.77Кб |
| 8. PCA objective function.mp4 |
3.68Мб |
| 8. PCA objective function.vtt |
2.28Кб |
| 8. Recommender RBM Code pt 2.mp4 |
39.58Мб |
| 8. Recommender RBM Code pt 2.vtt |
4.63Кб |
| 8. Testing greedy layer-wise autoencoder training vs. pure backpropagation.mp4 |
18.53Мб |
| 8. Testing greedy layer-wise autoencoder training vs. pure backpropagation.vtt |
1.86Кб |
| 8. Training an RBM (part 3) - Free Energy.mp4 |
27.58Мб |
| 8. Training an RBM (part 3) - Free Energy.vtt |
7.03Кб |
| 9. Cross Entropy vs. KL Divergence.mp4 |
7.42Мб |
| 9. Cross Entropy vs. KL Divergence.vtt |
5.48Кб |
| 9. PCA Application Naive Bayes.mp4 |
53.65Мб |
| 9. PCA Application Naive Bayes.vtt |
10.78Кб |
| 9. Proof that using Jupyter Notebook is the same as not using it.mp4 |
78.25Мб |
| 9. Proof that using Jupyter Notebook is the same as not using it.vtt |
78.26Мб |
| 9. RBM Greedy Layer-Wise Pretraining.mp4 |
23.62Мб |
| 9. RBM Greedy Layer-Wise Pretraining.vtt |
5.19Кб |
| 9. Recommender RBM Code pt 3.mp4 |
128.54Мб |
| 9. Recommender RBM Code pt 3.vtt |
11.98Кб |