Explore the advanced Retrieval-Augmented Generation (RAG) technique for enhancing large language models (LLMs) with external data integration. Learn how RAG improves response generation, especially for information not included in foundation models, making it valuable in corporate settings. Follow a step-by-step coding example using synthetic employee biographies to set up a RAG system, process large documents, and generate precise, contextually relevant responses. Discover how this approach enhances LLM output accuracy and aligns responses with organizational needs.
Overview
Syllabus
Question Answering over Documents with RAG (6.4)
Taught by
Jeff Heaton