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. Prerequisites: MAT-212, CSC-270, MAT-252, CSC-285 with a minimum grade of C.

Credits

3 credits

Prerequisite

MAT-212 and CSC-270 and MAT-252 and CSC-285 with a minimum grade of C.