Course Overview

Theoretical and practical issues in modern machine learning techniques. Topics include statistical foundations, supervised and unsupervised learning, decision trees, hidden Markov models, neural networks, and reinforcement learning. Minimal overlap with Computer Science 270.

Info

Instructor
Ron Parr
Office Hours: Monday 10:30 - 11:30, Wednesday 2:00 - 3:00
Office: D209 LSRC
Email: parr at cs dot duke dot edu

TA
Jason Pazis
Office Hours: Wednesday 3:00-4:00, Friday 12:00-1:00
Office: N208 North Bldg.
Email: jpazis at cs dot duke dot edu