Introduction to Machine Learning and Pattern Recognition
Description
Machine learning is the study of algorithms that learn how to perform a task from prior experience. This course introduces the student to machine learning concepts and techniques applied to pattern recognition problems in a diversity of application areas. Prerequisites: cumulative GPA of 4.50 or better over all major EECS courses (without second digit "5"); LE/EECS 2030 3.00 or LE/EECS 1030 3.00; one of SC/MATH 2030 3.00 or SC/MATH 2930 3.00 or SC/MATH 1131 3.00.
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