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Welcome to CIS520: Machine Learning

Lectures: Heilmeier Auditorium (Towne 100), MW 10:30–12:00, F 9:30am-11:00am . Lecture recordings are on Canvas, but note that lectures that use the board are very hard to follow from the recordings and that recordings sometimes fail

Prerequisites: Basic knowledge of linear algebra (matrices, eigenvectors), probability, statistics, programming,and latex. (See Course Description)

Notes: Lecture notes are under Lectures

Assignments: Assignments will be posted in Canvas; Your answers are submitted via canvas or, for code, using Turnin

Discussion: For questions on course material and assignments use Piazza

Matlab: For students registered in the class you can get a ‘free’ copy of matlab here. It can also be run on many of the student labs in the engineering school or remotely on biglab

Past years: last year’s site