Deep Learning Theory and Hands-On

3 credits · Graduate Programs

Advanced topics in deep learning including sequence models, attention and transformer architectures, generative networks, and model interpretability using XAI methods. Prerequisite(s): Admission to a graduate program in Mathematics and Statistics. Also known as: (formerly Statistics 601.28 (Deep Learning and Its Hands-On Practice))