CS 446

Fall 2014 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. Major theoretical paradigms and key concepts 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. Review of 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 2014
	CRN	Type	Section	Time	Day	Location	Instructor	Section Details
	46792	Lecture	D3	12:30PM -1:45PM	TR	Digital Computer Laboratory	Roth, D	Part of Term: 1 Date Range: 08/25/14-12/10/14 Credit: 3 hours
	46793	Lecture	D4	12:30PM -1:45PM	TR	Digital Computer Laboratory	Roth, D	Part of Term: 1 Date Range: 08/25/14-12/10/14 Credit: 4 hours Restriction(s): Restricted to Graduate - Urbana-Champaign.