PDAT 615G - Machine Learning

This course introduces the theory and practice of machine learning. Statistical learning techniques such as regression, regularization, and principal component analysis are covered. Programming in a popular machine learning language such as R is reviewed. Approaches such as neural networks, support vector machines, unsupervised learning, and reinforcement learning are covered.

Prerequisite: Successful completion of PDAT 610G - Introduction to Data Science. Graduate Students Only.
Credit(s): 3