MATH 213 - Supervised Machine Learning

Institution:

Lander University

Subject:

Mathematics

Description:

This course is an overview of machine learning techniques that use labeled data to train an algorithm to make predictions about unlabeled data. It provides an introduction to both linear regression and to classification techniques including logistic regression, K-nearest neighbors, support vector machines, tree-based methods, and neural networks. Prerequisites: DSCI 230, MATH 208, and MATH 211. Three credit hours.

Credits:

3.00

Credit Hours:

Prerequisites:

Corequisites:

Exclusions:

Level:

Instructional Type:

Lecture

Notes:

Additional Information:

Historical Version(s):

Institution Website:

www.lander.edu

Phone Number:

(864) 388-8000

Regional Accreditation:

Southern Association of Colleges and Schools

Calendar System:

Semester

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