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Unsupervised Deep Learning in Python
Introduction and Outline
Introduction and Outline (7:32)
Special Offer! Get the VIP version of this course (1:14)
Where does this course fit into your deep learning studies? (2:57)
How to Succeed in this Course (3:13)
Principal Components Analysis
What does PCA do? (6:14)
PCA derivation (4:22)
MNIST visualization, finding the optimal number of principal components (3:39)
PCA objective function (2:06)
t-SNE (t-distributed Stochastic Neighbor Embedding)
t-SNE Theory (4:28)
t-SNE on the Donut (5:51)
t-SNE on XOR (4:36)
t-SNE on MNIST (2:13)
Autoencoders
Autoencoders (3:20)
Denoising Autoencoders (1:55)
Stacked Autoencoders (3:32)
Writing the autoencoder class in code (11:55)
Writing the deep neural network class in code (12:42)
Testing greedy layer-wise autoencoder training vs. pure backpropagation (3:33)
Cross Entropy vs. KL Divergence (4:40)
Deep Autoencoder Visualization Description (1:32)
Deep Autoencoder Visualization in Code (11:14)
Restricted Boltzmann Machines
Restricted Boltzmann Machine Theory (9:32)
Deriving Conditional Probabilities from Joint Probability (6:18)
Contrastive Divergence for RBM Training (2:45)
RBM in Code + Testing a greedily pre-trained deep belief network on MNIST (14:24)
The Vanishing Gradient Problem
The Vanishing Gradient Problem Description (3:08)
The Vanishing Gradient Problem Demo in Code (12:17)
Extras + Visualizing what features a neural network has learned
Exercises on feature visualization and interpretation (2:07)
BONUS: How to derive the free energy formula (6:32)
BONUS: Application of PCA / SVD to NLP (Natural Language Processing)
BONUS: Application of PCA and SVD to NLP (Natural Language Processing) (2:30)
BONUS: Latent Semantic Analysis in Code (10:08)
BONUS: Application of t-SNE + K-Means: Finding Clusters of Related Words (8:38)
Appendix
What order should I take your courses in? (pt 1) (11:18)
What order should I take your courses in? (pt 2) (16:07)
How to Code by Yourself (part 1) (15:54)
How to Code by Yourself (part 2) (9:23)
How to Succeed in this Course (Long Version)
BONUS: Where to get discount coupons and FREE deep learning material (5:31)
Restricted Boltzmann Machine Theory
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