May 21 
Course Overview and Math Refresher 
Overview Slides
Logistics
Math Refresher

May 22 
Supervised Learning  I: KNN and Decision Trees 
Lecture Slides
Primer on Entropy
KNN Visualization
Decision Tree Visualization
Ipython Book
Spam Data

May 23 
Supervised Learning  II: Linear and Logistic Regression 
Lecture Slides
Ipython Notebook
Derivation For Linear/Ridge Regression
An intuitive explanation for Gradients

May 24 
Unsupervised Learning : Clustering and Dimensionality Reduction 
Lecture Slides
Comparison of PCA and Linear Regression
KMeans Demo

May 25 
Neural Networks 
Lecture Slides
Softmax Regression Notes

May 28 
Neural Networks and Backprop 
Lecture Slides
Cool Visualization of Neural Nets
Backprop on Simple Neural Net

May 29 
Model Fitting, Regularization and Ensembles 
Lecture Slides
Blog on Gradient Descent Variants and Optimization

May 30 
Deep Learning for Images 
Lecture Slides 
May 31 
Practical Implementations and Deep Learning Choices 
Lecture Slides
Machine Learning for NLP1
Code Tutorial 
June 1 
Machine Learning for Natural Language 
Machine Learning for NLP2
Course Wrap up
Chris Olah's Blog
Karpathy's Blog
