CPSC 6430 - Machine Learning: Impl & Eval

Institution:

Clemson University

Subject:

Computer Science

Description:

Students learn to code machine learning algorithms from basic principles, without machine learning libraries. Topics include supervised learning such as regression and classification; unsupervised learning, such as clustering; and measures of performance such as bias/variance theory, measures, and error metrics. Students must be familiar with principles of probability and statistics and must have programming experience when enrolling in this course.

Credits:

3.00

Credit Hours:

Prerequisites:

Corequisites:

Exclusions:

Level:

Instructional Type:

Lecture

Notes:

Additional Information:

Historical Version(s):

Institution Website:

www.clemson.edu

Phone Number:

(864) 656-4636

Regional Accreditation:

Southern Association of Colleges and Schools

Calendar System:

Semester

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