Deep Learning

Catalog description

Credits 3. 3 Lecture Hours. Basic concepts in neural computing; functional equivalence and convergence properties of neural network models; associative memory models; associative, competitive and adaptive resonance models of adaptation and learning; selective applications of neural networks to vision, speech, motor control and planning; neural network modeling environments. Prerequisites: MATH 251 and MATH 304 or approval of instructor.