STAT 253 - Statistical Machine Learning

The linear and logistic modeling techniques from STAT 155 are augmented with the three foundational machine learning tasks: regression, classification, and clustering. The course explores techniques central to these tasks, including methods of data exploration, supervised and unsupervised learning, parametric and nonparametric modeling, and model training and evaluation. As required by the application of these sophisticated techniques, the course also introduces foundational statistical computer programming concepts. Prerequisite(s): STAT 155 . Every semester. (4 Credits)