Units: 4
Hours: Lecture, 3 hours; discussion, 1 hour
Catalog page 480
Prerequisites: MATH 161B with a grade of C- or better
Description: Exploration of essential mathematical concepts for artificial intelligence, covering natural language processing, generative networks, and reinforcement learning. Topics include text classification, multimodal learning, and advanced generative models (GANs, diffusion models). Emphasizes domain adaptation, semi-supervised, and self-supervised learning with applications in real-world AI tasks.