CS150 -- Topics in Computer Science:
Machine Learning
Fall, 2009

(last updated 8/31/2009)


Wayne Iba,
office: Math and Computer Science Building,
phone: (805)565-6799
Office hours: see my main page
Mitchell, Tom. (1997).  Machine Learning.  McGraw Hill.  ISBN 0071154671 (international paperback) or 0070428077 (hardback).  [required]

Time and place: MWF, 2:00-3:05am; Murchison Gym Room 2

Official Syllabus

Tentative class schedule (see Eureka pages)

One reason I find artificial intelligence so interesting is the opportunity to think about the nature of thinking. About the only thing that is cooler than that is learning how learning takes place. When we focus on computational mechanisms that model and exhibit learning, we are studying machine learning. This topics-course will survey the range of methods that allow us to write programs that improve their performance as a result of experience (i.e., learn).

The course will be organized as a seminar with some small project components. Students will give multiple presentations on material from the text or other assigned readings. They will also implement some of the techniques we will be studying and demonstrate the systems' learning behavior in code walks and demonstrations using real-world data sets.