COMP 572 - Neural Networks

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Description

Hours: Three hours lecture in the lab per week Prerequisites: Admission to the Computer Science or Mathematics Graduate Program Covers the basic ideas of distributed computation with many simple processing units, similar to the neurons of the brain. Topics include: Hopfield style networks applied to optimization problems, and the backpropagation method applied to pattern classification problems. Additional topics include associate memory, binary vs. analog networks, simulated annealing.

Units: 3.00
Grading: Letter Grade

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Session Section Class # Type Days Time Location Instructor Course Details [Key]
E1 1 4159 LEC M  6:00 PM  -  8:50 PM  Bell Tower 1481 Andrzej Bieszczad Course Open Class Details Extended University Class In Person Class

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