DSCI 440W - Machine Learning & Data Mining

4 credit(s)
Introduction to machine learning techniques and their applications. Covers standard learning methods such as linear regression, neural networks, decision trees, support vector machines, naive Bayes, and nearest neighbors. Provides experience implementing, applying, and assessing the accuracy of machine learning methods to data science problems.
Offered: Offered alternate years

Core Requirement(s): Counts toward core requirement: Writing in the Discipline
Prerequisite(s): DSCI 340 with a minimum grade of C. MATH 206 (may be taken concurrently).