Northwestern University 1 credit Computer Science
In the first half of this course, we will explore the evolution of deep neural network language models, starting with n-gram models and proceeding through feed-forward neural networks, recurrent neural networks, transformer-based models and large language models. We will incorporate classic NLP techniques when covering these architectures. In the second half of the course we will explore advances in prompting, parameter efficient fine-tuning, ensemble models, retrieval augmented generation and agentic AI. Prerequisites: COMP_SCI 349 or permission of instructor.
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