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: Alternate years

Core Requirement(s): Writing in the Discipline
Prerequisite(s): DSCI 340 and MATH 306 each with a minimum C grade. (MATH 306 may be taken concurrently).