An exploration of multi-layered machine learning architectures as applied to problems in a variety of domains. The course will study various network architectures including deep feed-forward, convolutional and recurrent networks, and uses in both supervised and unsupervised learning. Students will implement solutions in different problem domains, and learn to effectively manage practical and domain-specific issues that affect model performance.
Prerequisite(s): CSCI 5750
|Spring 2021||Abby Stylianou||MWF 2:10pm-3:00pm|