Fall 2005 Course Descriptions

COMP 150-ML Special Topics: Machine Learning

R. Khardon
TR 5:30p-6:45p, Halligan Hall 106
M+ Block

The course covers the main paradigms in machine learning including supervised learning, unsupervised learning and reinforcement learning. The focus is on practical aspects: ideas underlying various methods, design of algorithms using these ideas, and their empirical evaluation. We will discuss well established techniques as well as new developments from recent research.

Prerequisite: Comp 160 or consent.


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