Course Description
Pre-Requisite(s):
Calculus, Basic linear algebra, Basic Probability and Basic Algorithm
This is a graduate-level machine learning course. Machine Learning is concerned with computer programs that automatically improve their performance through experience. This course covers introductory topics about the theory and practical algorithms for machine learning from a variety of perspectives. Topics include supervised learning, unsupervised learning and learning theory. Statistics is recommended. Students should already have good programming skills.
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