CS 274A: Background Notes and Reading, Winter 2018

Note that the contents of this page may be updated before the quarter starts or during the quarter.

Notes (Note Sets 1 to 3 are particularly relevant for the 1st and 2nd week)

Textbooks (recommended for background reading but not required)

General Background/Review Material on Probability :
Learning from Data using Maximum Likelihood

Bayesian Learning

Optimization Methods for Machine Learning

Regression Models

Probabilistic Classification

The EM Algorithm, Mixture Models, and Probabilistic Clustering

State-Space and Time-Series Models

Sampling Methods