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Machine Learning
CS 6375
Erik Jonsson School of Engineering and Computer Science
Algorithms for training perceptions and multi-layer neural nets: back propagation, Boltzmann machines, and self-organizing nets. The ID3 and the Nearest Neighbor algorithms. Formal models for analyzing learnability: exact identification in the limit and probably approximately correct (PAC) identification. Computational limitations of learning machines. 3 credit hours.
Prerequisite: CS 5343.
Offering Frequency: Each year
Grades: 3,925
Median GPA: A-
Mean GPA: 3.635
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Machine Learning
CS 6375
Erik Jonsson School of Engineering and Computer Science
Algorithms for training perceptions and multi-layer neural nets: back propagation, Boltzmann machines, and self-organizing nets. The ID3 and the Nearest Neighbor algorithms. Formal models for analyzing learnability: exact identification in the limit and probably approximately correct (PAC) identification. Computational limitations of learning machines. 3 credit hours.
Prerequisite: CS 5343.
Offering Frequency: Each year
Grades: 3,925
Median GPA: A-
Mean GPA: 3.635
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