Explore the concept of Retrieval Augmented Generation (RAG) in this 48-minute video from Data Science Dojo. Learn how RAG enhances large language model (LLM) performance by incorporating external knowledge sources. Discover the process of converting external data into numerical representations, appending relevant context to user prompts, and generating more accurate responses. Understand the advantages of RAG, including its ability to address domain-specific tasks, personalize for specialized fields, and maintain up-to-date information. Watch a practical demonstration and participate in a Q&A session. Gain insights into the potential of RAG to revolutionize LLM applications across various industries.
Retrieval Augmented Generation - Boosting LLM Performance with External Knowledge
Overview
Syllabus
– Introduction to RAG
– Large Language Models
– Retrieval Augmented Generation
– Pros and Cons of RAG
– Demo
– QnA
Taught by
Data Science Dojo
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