Machine Learning

This course introduces fundamental concepts and techniques supervised and unsupervised learning. Topics include basic probability and statistics, supervised learning through neural networks, dimensionality reduction, nearest neighbor methods, optimal decision boundaries, kernel methods, evolutionary learning, reinforcement learning, tree-based learners, unsupervised learning, and deep belief networks. PREREQ: STAT 2246, COSC 2516 Introduction to Data Analytics, COSC 3707. (lec 3) cr 3

COSC-4556EL
Mathematics & Computer Science
3.00
UG