DSCI 440 - Machine Learning and 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.

Prerequisite(s): DSCI 340 and MATH 307, each with a minimum grade of C; MATH 206 (may be taken concurrently)