CS 446

Fall 2008 Part of Term 1

Part of Term 1
Aug 25-Dec 10

Machine Learning

Credit: 3 OR 4 hours.

Theory and basic techniques in machine learning. Presents the main theoretical paradigms and key ideas developed in machine learning in the context of applications such as natural language and text processing, computer vision, data mining, adaptive computer systems and others. Reviews several supervised and unsupervised learning approaches: methods for learning linear representations; on-line learning, Bayesian methods; decision-trees; features and kernels; clustering and dimensionality reduction.

3 undergraduate hours. 3 or 4 graduate hours. Prerequisite: CS 373 and CS 440.

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CS 446 class schedule data for fall 2008
	CRN	Type	Section	Time	Day	Location	Instructor	Section Details
	46792	Lecture	D3	9:30AM -10:45AM	TR	Siebel Center for Comp Sci	Roth, D	Part of Term: 1 Date Range: 08/25/08-12/10/08 Credit: 3 hours
	46793	Lecture	D4	9:30AM -10:45AM	TR	Siebel Center for Comp Sci	Roth, D	Part of Term: 1 Date Range: 08/25/08-12/10/08 Credit: 4 hours Restriction(s): Restricted to Graduate - Urbana-Champaign.