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CPTR4100 Machine Learning

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CRS Acad Level: UG

Course #: CPTR4100

Credits: 3

About the Course:

The field of machine learning is concerned with the question of how to construct computer programs that improve automatically with experience. In recent years, many successful applications of machine learning have been developed, ranging from data-mining programs that learn to detect fraudulent credit card transactions, to autonomous vehicles that learn to drive on public highways. At the same time, there have been important advances in the theory and algorithms that form the foundation of this field. Theoretical properties of these algorithms and their practical applications will be covered. Machine learning algorithms to be studied include: decision trees, artificial neural networks, Bayesian learners, evolutionary algorithm, boosting and bagging techniques, computational learning theory, and PAC learnability. The course will also introduce students to Map Reduce algorithms for pattern discovery in massive unstructured data. Prerequisite: Successful completion of CPTR1100 or CPTR1400, and MATH2200, MATH2202, and MATH3305.

UPDATED! Fall 2020 plansClick here