This lecture covers a few things that will complete our study of unsupervised learning

     1.  code for running kMeans on AWS

     2.  code for fitting Gaussian mixture model using EM algo

We'll also run through an intro to supervised learning in preparation for the algorithms that we'll cover.  Here are some references that we'll use. 

http://www-users.cs.umn.edu/~kumar/dmbook/dmslides/chap4_basic_classification.pdf

After regular class session tonight we'll have a session to go through the detailed mathematics for the EM algorithm. Here's a pdf of the notes we'll use.

EM_algorithm.pdf