This page refers to the Fall 2010 offering of CSE 574 only. The information on this page does not necessarily apply to every offering of CSE 574.
Fall 2010
11020
Introduction to Machine Learning
Involves teaching computer programs to improve their performance through guided training and unguided experience. Takes both symbolic and numerical approaches. Topics include concept learning, decision trees, neural nets, latent variable models, probabilistic inference, time series models, Bayesian learning, sampling methods, computational learning theory, support vector machines, and reinforcement learning.
CSE 250 and any of EAS 305/308, STA 401/421, MTH 309; or permission of instructor.
Ph.D.: This course fulfills one Artificial Intelligence Core Course requirement.
M.S.: This course fulfills one Artificial Intelligence Core Course requirement.