Artificial Neural Networks. ((3 Credits))

Catalog description

Prerequisite(s): MATH 1210 and University Advanced Standing Introduces a range of topics in the field of artificial neural networks: modeling of brains, applicable algorithms, and related applications. Develops the theory of a number of neural network models such as Perceptron, Multilayer Perceptron, and Hopefield networks. Emphasizes algorithms for implementing simple artificial neural networks and their applications. Lab access fee of $45 for computers applies. Course lab fee of $50 for materials applies. Software fee of $50 applies.