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Machine Learning

A survey of the field of machine learning, with an introduction to the fundamental algorithms in the field and the theory underpinning them. Topics include techniques for regression, classification, ensemble methods, and dimensionality reduction.

Counts towards the Mathematics major and minor.
Counts towards the Computer Science major and minor.
Counts as an elective in the Data Science interdisciplinary minor.


Prerequisites:

Proficiency in a high-level programming language and data structures, at the level expected in CSC 221, and MAT/CSC 220 (or permission of the instructor). 

Offered Spring of even-numbered years.