Machine Learning

Catalog description

This course provides an introduction to supervised and unsupervised learning (e.g., support vector machines, neural networks, k-nearest neighbor classifier, logistic and least squares regression), clustering methods, dimensionality reduction techniques (e.g., principal component analysis), and reinforcement learning theory. Prerequisite(s): grade of C or better in A MAT 220, A MAT 367 or A MAT 370, and I CSI 401.