Computer Science 335 - Machine Learning

Fall
2014
01
4.00
Daniel Sheldon
TTH 10:00AM-11:15AM;F 10:00AM-10:50AM
Mount Holyoke College
89677
Clapp Laboratory 218;Clapp Laboratory 218
dsheldon@mtholyoke.edu
How does Neflix 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.
Permission is required for interchange registration during the add/drop period only.