CSCI 1950F - Introduction to Machine Learning

Institution:

Brown University

Subject:

Description:

How can artificial systems learn from examples, and discover information buried in massive datasets? This course explores the theory and practice of statistical machine learning. Topics include parameter estimation, probabilistic graphical models, approximate inference, and kernal and nonparametric methods. Applications to regression, categorization, and clustering problems are illustrated by examples from vision, language, communications, and bioinformatics. Prerequisites: CSCI 0160, 0180, or 0190, and comfort with basic probability, linear algebra, and calculus.

Credits:

1.00

Credit Hours:

Prerequisites:

Corequisites:

Exclusions:

Level:

Instructional Type:

Lecture

Notes:

Additional Information:

Historical Version(s):

Institution Website:

www.brown.edu

Phone Number:

(401) 863-1000

Regional Accreditation:

New England Association of Schools and Colleges

Calendar System:

Semester

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