1. Introduction and Outline

  1. Introduction and Outline.vtt

  2. Where does this course fit into your deep learning studies.vtt

  3. How to Succeed in this Course.vtt

  4. Where to get the code and data.vtt

  5. Tensorflow or Theano - Your Choice!.vtt

  6. What are the practical applications of unsupervised deep learning.vtt

 10. Basics Review

  1. (Review) Theano Basics.vtt

  2. (Review) Theano Neural Network in Code.vtt

  3. (Review) Tensorflow Basics.vtt

  4. (Review) Tensorflow Neural Network in Code.vtt

  5. (Review) Keras Basics.vtt

  6. (Review) Keras in Code pt 1.vtt

  7. (Review) Keras in Code pt 2.vtt

 11. Optional - Legacy RBM Lectures

  1. (Legacy) Restricted Boltzmann Machine Theory.vtt

  2. (Legacy) Deriving Conditional Probabilities from Joint Probability.vtt

  3. (Legacy) Contrastive Divergence for RBM Training.vtt

  4. (Legacy) How to derive the free energy formula.vtt

 12. Appendix

  1. What is the Appendix.vtt

  10. Python 2 vs Python 3.vtt

  11. Is Theano Dead.vtt

  12. What order should I take your courses in (part 1).vtt

  13. What order should I take your courses in (part 2).vtt

  2. BONUS Where to get Udemy coupons and FREE deep learning material.vtt

  3. Windows-Focused Environment Setup 2018.vtt

  4. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.vtt

  5. How to Code by Yourself (part 1).vtt

  6. How to Code by Yourself (part 2).vtt

  7. How to Succeed in this Course (Long Version).vtt

  8. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.vtt

  9. Proof that using Jupyter Notebook is the same as not using it.vtt

 2. Principal Components Analysis

  1. What does PCA do.vtt

  10. SVD (Singular Value Decomposition).vtt

  2. How does PCA work.vtt

  3. Why does PCA work (PCA derivation).vtt

  4. PCA only rotates.vtt

  5. MNIST visualization, finding the optimal number of principal components.vtt

  6. PCA implementation.vtt

  7. PCA for NLP.vtt

  8. PCA objective function.vtt

  9. PCA Application Naive Bayes.vtt

 3. t-SNE (t-distributed Stochastic Neighbor Embedding)

  1. t-SNE Theory.vtt

  2. t-SNE Visualization.vtt

  3. t-SNE on the Donut.vtt

  4. t-SNE on XOR.vtt

  5. t-SNE on MNIST.vtt

 4. Autoencoders

  1. Autoencoders.vtt

  10. Deep Autoencoder Visualization Description.vtt

  11. Deep Autoencoder Visualization in Code.vtt

  12. An Autoencoder in 1 Line of Code.vtt

  2. Denoising Autoencoders.vtt

  3. Stacked Autoencoders.vtt

  4. Writing the autoencoder class in code (Theano).vtt

  5. Testing our Autoencoder (Theano).vtt

  6. Writing the deep neural network class in code (Theano).vtt

  7. Autoencoder in Code (Tensorflow).vtt

  8. Testing greedy layer-wise autoencoder training vs. pure backpropagation.vtt

  9. Cross Entropy vs. KL Divergence.vtt

 5. Restricted Boltzmann Machines

  1. Basic Outline for RBMs.vtt

  10. RBM in Code (Theano) with Greedy Layer-Wise Training on MNIST.vtt

  11. RBM in Code (Tensorflow).vtt

  2. Introduction to RBMs.vtt

  3. Motivation Behind RBMs.vtt

  4. Intractability.vtt

  5. Neural Network Equations.vtt

  6. Training an RBM (part 1).vtt

  7. Training an RBM (part 2).vtt

  8. Training an RBM (part 3) - Free Energy.vtt

  9. RBM Greedy Layer-Wise Pretraining.vtt

 6. The Vanishing Gradient Problem

  1. The Vanishing Gradient Problem Description.vtt

  2. The Vanishing Gradient Problem Demo in Code.vtt

 7. Extras + Visualizing what features a neural network has learned

  1. Exercises on feature visualization and interpretation.vtt

 8. Applications to NLP (Natural Language Processing)

  1. Application of PCA and SVD to NLP (Natural Language Processing).vtt

  2. Latent Semantic Analysis in Code.vtt

  3. Application of t-SNE + K-Means Finding Clusters of Related Words.vtt

 9. Applications to Recommender Systems

  1. Recommender Systems Section Introduction.vtt

  10. Recommender RBM Code Speedup.vtt

  2. Why Autoencoders and RBMs work.vtt

  3. Data Preparation and Logistics.vtt

  4. AutoRec.vtt

  5. AutoRec in Code.vtt

  6. Categorical RBM for Recommender System Ratings.vtt

  7. Recommender RBM Code pt 1.vtt

  8. Recommender RBM Code pt 2.vtt

  9. Recommender RBM Code pt 3.vtt