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Spring 2020
Sep 23, 2019
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CSCI 2430 - Topics in Machine Learning
Machine learning from the artificial intelligence perspective, with emphasis on empirical validation of learning algorithms. Different learning problems are considered, including concept learning, clustering, speed-up learning, and behavior learning. For each problem a variety of solutions are investigated, including those from symbolic AI, neural and genetic algorithms, and standard statistical methods. Prerequisite: CSCI 1410 or familiarity with basic logic and probability theory.
1.000 Credit hours
1.000 Lecture hours

Levels: Graduate, Undergraduate
Schedule Types: Primary Meeting

Computer Science Department

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