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Neural Networks

Course CodeCOMP-258
Lecture hours per week2
Lab hours per week2
Course AvailabilityOpen
Description

This course covers artificial neural networks and their practical applications. Coursework emphasizes fundamental models and algorithms starting with McCulloch-Pitts and Perceptron models, Multi-Layer Perceptron (MLP) networks, backpropagation algorithm, activation functions, convolutional neural networks, and recurrent neural networks. Students will gain hands-on experience by using Keras and TensorFlow to build and train models for solving various classification/prediction problems.

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