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.
Prerequisite
CSC-285 and
MAT-212 must be completed with a grade of C or higher prior to taking this course.