Computer Science 335 - Machine Learning

How does Netflix learn what movies a person likes? How do computers read handwritten addresses on packages, or detect faces in images? Machine learning is the practice of programming computers to learn and improve through experience, and it is becoming pervasive in technology and science. This course will cover the mathematical underpinnings, algorithms, and practices that enable a computer to learn. Topics will include supervised learning, unsupervised learning, evaluation methodology, and Bayesian probabilistic modeling. Students will learn to program in MATLAB or Python and apply course skills to solve real world prediction and pattern recognition problems. Programming Intensive.

Prereq: A grade of C or better in COMSC-205, MATH-232, and a Calculus course (MATH-101, MATH-102, or MATH-203).