CS4315 Introduction to Machine Learning and Data Mining

A survey of methods by which software and hardware can improve their performance over time. Topics include data manipulation, concept learning, association rules, decision trees, Bayesian models, simple linear models, case-based reasoning, genetic algorithms, and finite-state sequence learning. Students will do projects with software tools. Prerequisites: One college-level course in programming.

Prerequisite

CS3000 and one college-level course in programming

Lecture Hours

3

Lab Hours

1

Quarter Offered

  • Winter