Homeworks

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.

Homework1:
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.

Homework2:
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.

Homework3:
Here are the 4 data files: hw3train.dat,hw3test.dat, digitsTrain.dat,digitsTest.dat. Here is a skeleton file to visualize the digits.

Homework4:
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.