Introduction to Data Science and Statistics Learning ((3 Credits))

Catalog description

This course introduces theory and applications for statistics learning techniques including maximal marginal classifiers, support vector machines, K-means and hierarchical clustering, and re-sampling methods. R programming will be used throughout the course.