CS 446

Spring 2018 Part of Term 1

Part of Term 1
Jan 16-May 2

Machine Learning

SHOW FINAL EXAM SCHEDULE

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 spring 2018
CRN	Type	Section	Time	Day	Location	Instructor	Section Details
31421	Lecture-Discussion	P3	6:00PM -7:15PM	TR	Electrical & Computer Eng Bldg	Schwing, A Telgarsky, M	Part of Term: 1 Date Range: 01/16/18-05/02/18 Credit: 3 hours
39433	Lecture-Discussion	P4	6:00PM -7:15PM	TR	Electrical & Computer Eng Bldg	Schwing, A Telgarsky, M	Part of Term: 1 Date Range: 01/16/18-05/02/18 Credit: 4 hours Restriction(s): Restricted to Graduate - Urbana-Champaign.
68039	Lecture-Discussion	R3	6:00PM -7:15PM	TR	Electrical & Computer Eng Bldg	Schwing, A Telgarsky, M	Part of Term: 1 Date Range: 01/16/18-05/02/18 Credit: 3 hours
68040	Lecture-Discussion	R4	6:00PM -7:15PM	TR	Electrical & Computer Eng Bldg	Schwing, A Telgarsky, M	Part of Term: 1 Date Range: 01/16/18-05/02/18 Credit: 4 hours Restriction(s): Restricted to Graduate - Urbana-Champaign.