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• file:README.md
• file:846480_d909.jpg
• file:3. Application of t-SNE + K-Means Finding Clusters of Related Words.vtt
• file:2. Latent Semantic Analysis in Code.vtt
• file:1. Application of PCA and SVD to NLP (Natural Language Processing).vtt
• file:1. Exercises on feature visualization and interpretation.vtt
• file:2. The Vanishing Gradient Problem Demo in Code.vtt
• file:9. RBM Greedy Layer-Wise Pretraining.vtt
• file:8. Training an RBM (part 3) - Free Energy.vtt
• file:5. Neural Network Equations.vtt
• file:4. Intractability.vtt
• file:9. Cross Entropy vs. KL Divergence.vtt
• file:8. Testing greedy layer-wise autoencoder training vs. pure backpropagation.vtt
• file:7. Autoencoder in Code (Tensorflow).vtt
• file:6. Writing the deep neural network class in code (Theano).vtt
• file:5. Testing our Autoencoder (Theano).vtt
• file:5. t-SNE on MNIST.vtt
• file:3. t-SNE on the Donut.mp4
• file:2. t-SNE Visualization.vtt
• file:9. PCA Application Naive Bayes.vtt
• file:8. PCA objective function.vtt
• file:7. PCA for NLP.vtt
• file:6. PCA implementation.vtt
• file:5. MNIST visualization, finding the optimal number of principal components.vtt