Machine Learning is the study of algorithms that improve automatically through experience. Topics covered typically include Bayesian learning, decision trees, genetic algorithms, Markov models and neural networks. The course goals include:
To expose students to concepts and methods in machine learning.
To give students a basic set of machine learning tools applicable to a variety of problems.
To teach students critical analysis of machine learning approaches so that the student can determine when a particular technique is applicable to a given problem.
Course Information
prerequisites: Significant prior programming experience (Equivalent to CS 211), graduate standing, or instructor permission
location of classroom: Tech LG68
days and hours class meets: Mon, Wed, Fri 1:00pm - 1:50pm
textbook(s): Machine Learning, Tom Mitchell, McGraw Hill, 1997
supplementary reading: Selected papers, assigned in class
Instructor
name: Bryan Pardo
office location: 3.323 Ford Building
office phone number: 847 491 7184
email: go to www.northwestern.edu and search for 'Bryan Pardo'
office hours: 3-4pm Wednesdays
Teaching Assistant
name: Forrest Stonedahl
email: forrest@northwestern.edu
office location: 3.215 Ford Building
office hours: 2-3pm Tuesdays, and flexible hours by appointment
