Machine Learning

Catalog description

Introduces Machine Learning and its core models and algorithms by examining techniques in both supervised and unsupervised learning. Algorithms under consideration are regression, decision trees, neural networks, support vector machines, and clustering algorithms. Concepts and algorithms will be implemented using the statistical software program R. Prerequisite: STAT-266.