CS 274A: Background Notes and Reading, Winter 2017

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