Stat406 (Algorithms for classification and prediction) Spring 2010 (term 2)

MWF 1-2, Math 225, Lab W 4-5 LSK 302.

Synoposis: This is a senior-level undergraduate class on machine learning, covering the foundations, such as (Bayesian) statistics and information theory, and then focusing on supervised learning (classification, regression).

Textbook: Draft copies of my textbook, Machine Learning: a probabilistic approach, will be made available for purchase on Jan 2nd, 2010, for about $60.

Pre-requisites. Linear algebra, calculus, probability theory, programming (preferably R or Matlab), some previous class on machine learning (eg CS 340) or applied statistics (eg Stat 306).