MAT-427 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.

Credits

3 credits

Prerequisite

MAT-212, MAT-252, CSC-270, and CSC-285 must each be completed with a grade of C or better prior to taking this course.