MATH-4025 Statistical Machine Learning

A study of methods to construct and evaluate predictive models. Topics may include lasso and ridge regression, Naive Bayes, random forests, support vector machines, gradient boosting, and neural networks. The course will require a significant data analysis and modeling project. Formerly MAT-427.

Credits

4 credits

Prerequisite

CSCI-2025 and MATH-2025, each with a grade of C or better