DSC 528 - Deep Learning

CSC 546 or DSC 511. (4)

Study of fundamental principles, mathematical foundations, and implementations of deep learning. Topics include methods such as gradient descent and backpropagation used to optimize models; model types such as linear, pooling and convolutional layers; and common neural network architectures, with applications from computer vision to natural language processing. Not open to students with credit for DSC 428. Graded ABCDE