ENGN2520

Pattern Recognition and Machine Learning

Instructor(s):
Pedro Felzenszwalb
Course Home Page:
Location: Barus & Holley 159
Meeting Time: K: TTh 2:30-3:50
Exam Group: 11
Semester: 2 (Spring)
Offered This Year?  Yes
When Offered? Every Year

Description

This course covers fundamental topics in pattern recognition and machine learning. We will consider applications in computer vision, signal processing, speech recognition and information retrieval. Topics include: decision theory, parametric and non-parametric learning, dimensionality reduction, graphical models, exact and approximate inference, semi-supervised learning, generalization bounds and support vector machines. Prerequisites: basic probability, linear algebra, calculus and some programming experience.

CRN: 27449