Supervised Learning II

Course ID DSCI 572

Campus Computational Linguistics

Semester Winter

Course Block 4

Course Description How do modern neural networks learn? This course introduces the mathematical foundations of deep learning and optimization, Topics include optimization methods from gradient descent to Adam and Muon optimizers, architectures ranging from fully connected networks to transformers, and various methods for language modeling, with a focus on mathematical derivation and code implementation.

Instructor(s) with link Jian Zhu