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CMSC422

Introduction to Machine Learning

Prerequisite: Minimum grade of C- in CMSC320, CMSC330, and CMSC351; and 1 course with a minimum grade of C- from (MATH240, MATH461); and permission of CMNS-Computer Science department. Machine Learning studies representations and algorithms that allow machines to improve their performance on a task from experience. This is a broad overview of existing methods for machine learning and an introduction to adaptive systems in general. Emphasis is given to practical aspects of machine learning and data mining. Credit only granted for CMSC422 or CMSC498M.

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Average GPA: 3.07 between 1,322 students

"W"s are considered to be 0.0 quality points. "Other" grades are not factored into the average GPA calculation.