EE 182
Large Language Models
The class focuses on large language models (LLMs) and language-and-vision models, as well as on generative methods for artificial intelligence (AI). Topics include deep neural networks, transformers, large language models, generative adversarial networks, diffusion models, state-space models, and applications of such architectures and methods to image analysis, image synthesis, and text-to-image translation.
Topics
- deep neural networks
- transformers
- large language models
- generative adversarial networks
- diffusion models
- state-space models
- and applications of such architectures and methods to image analysis
- image synthesis
- and text-to-image translation
Topics explicitly listed in official catalogue description
Prerequisites & course information
Prerequisites: EE/CMS/CNS/CS/IDS 181 and experience programming in Python, Numpy, and PyTorch. Background in algorithms, linear algebra, calculus, probability, and statistics is highly recommended..
Catalogue variants
- Large Language Models · 12 units (3-3-6) | third term