CSCI5527: Deep Learning: Models, Computation, and Applications
3 Credits
This course introduces the basic ingredients of deep learning, describes effective models and computational principles, and samples important applications. Topics include universal approximation theorems, basics of numerical optimization, auto-differentiation, convolution neural networks, recurrent neural networks, generative neural networks, representation learning, and deep reinforcement learning.
Prerequisite: CSCI 5521 or equivalent
Maturity in linear algebra, calculus, and basic probability is assumed. Familiarity with Python is necessary to complete the homework assignments and final project.