CS 446 - Machine Learning

Institution:

University of Illinois at Urbana-Champaign

Subject:

Description:

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.

Credits:

3.00 - 4.00

Credit Hours:

Prerequisites:

Corequisites:

Exclusions:

Level:

Instructional Type:

Lecture

Notes:

Additional Information:

Historical Version(s):

Institution Website:

www.illinois.edu/

Phone Number:

(217) 333-1000

Regional Accreditation:

North Central Association of Colleges and Schools

Calendar System:

Semester

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