2017 Fall Term
Computer Science 732
This course provides a broad introduction to machine learning and pattern recognition. Topics include but are not limited to Bayesian Inference, SVMs, Clustering and Classification, Decision Trees and Ensemble Methods. Particular focus will be placed on the theoretical understanding of these methods, as well as their practical applications.
Other Requirements: PREREQ: ADMISSION TO GRADUATE PROGRAM IN COMPUTER SCIENCE
- This schedule is informational and does not guarantee availability for registration.
- Sections may be full or not open for registration. Please use WINS if you wish to register for a course.
|Section Details||Meeting Details & Topic||Instructor||Syllabus|
|09/06 - 12/22 (1)||Th 5:00 PM - 7:30 PM||