STAT 652 - Statistical Learning

Units: 2
Statistical machine learning overview. Choosing a learning algorithm. Unsupervised learning including classification methods, nearest neighbors, naïve Bayes, decision trees and rules, neural networks, k-means. Supervised learning including linear regression and logistic regression. Model performance and evaluation. Confusion matrix. Report writing.

Prerequisites: Post-baccalaureate standing.
Equivalent Quarter Course: STAT 6620.
Possible Instructional Methods: Entirely On-ground.
Grading: A-F grading only.