Mathematics for Machine Learning credit:

4 Hours

Overview of the major components of modern machine learning, including linear and logistic regression, Principal Component Analysis, Support Vector Machines, feature importance, casual inference, training, validation and testing. Students will learn how to connect their mathematical background with various tools in data science, emphasizing the connection between modeling and analysis as well as modern data science tools. 4 undergraduate hours. No graduate credit. Prerequisite: MATH 416 ; MATH 461 or STAT 400 ; STAT 207 ; CS 277 ; and CS 307 .