CS 737 - Machine Learning

(3.00 cr.)

Introduces core machine learning models and algorithms for classification, regression, clustering, and dimensionality reduction. The course focuses on both understanding the theory of learning approaches, and effectively using them to solve real-world data science problems. Topics include least squares methods, linear classification, support vector machines, Bayesian networks and inference, the EM algorithm, and kernel methods.

Prerequisite: CS 703 .
Sessions Typically Offered: Spring
Years Typically Offered: Annually