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COMP 4107 [0.5 credit] Neural Networks

Theory and application of neural networks to problems in machine learning. Topics include: biological models, perceptron and other neuron types, feed forward and recurrent architectures, learning algorithms and applications in pattern recognition and sequence prediction.
Includes: Experiential Learning Activity
Prerequisite(s): COMP 2804, one of COMP 2404, SYSC 3010, SYSC 3110 and one of MATH 1104 or MATH 1107.
Lectures three hours a week.