3 Credit Hours
This course introduces students to the fundamental methods used in neural networks. Topics include single and multi-layer perceptrons, radial-basis function networks, support vector machines, stochastic machines, and deep networks, supervised and unsupervised learning, application to pattern classification and function approximation problems.