Homework0 (not graded):
Go through this matlab tutorial (see this page for running matlab at UCI) and this set of background notes on linear algebra and probability from Hal Daume.
Here is data required for the programming portion, and here is skeleton code to help you get started. A good reference for the material from class is this writeup from Andrew Ng.
Here is training and testing data required for the programming portion. Here is a note on the IRLS algorithm. The writeup from Ng has a section on GLMs, and a useful reference for Newton-Raphson optimization and class conditional guassian modelling is this paper from Michael Jordan.
Here are the 4 data files: hw3train.dat,hw3test.dat, digitsTrain.dat,digitsTest.dat. Here is a skeleton file to visualize the digits.
Here are the 4 data files: hw4train.dat,hw4test.dat, faceTrain.dat ,faceTest.dat. Here is a useful reference on kernel PCA. Here is quadprog2.m if needed.