Pattern Recognition and Machine Learning
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||K: TTh 2:30-3:50
||11: 12/18/2015 at 9:00 A.M.
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This course is offered as CSCI 1420 for computer science students
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.