Practical Retrieval Augmented Generation (RAG)
English | Tutorial | Size: 1.35 GB
4+ Hours of Video Instruction
Start building, evaluating, and iterating on retrieval augmented generation (RAG) systems today!
Practical Retrieval Augmented Generation shows you how to improve existing large language models by giving them the ability to access additional information that was not part of their original training data.
About the Instructor:
Sinan Ozdemir is the founder and CTO of LoopGenius where he uses state-of-the-art AI to help people create and run their businesses. Sinan is a former lecturer of data science at Johns Hopkins University and the author of multiple textbooks on data science and machine learning. Additionally, he is the founder of the recently acquired Kylie.ai, an enterprise-grade conversational AI platform with RPA capabilities. Sinan holds a master’s degree in pure mathematics from Johns Hopkins University and is based in San Francisco, California.
Learn How To:
Develop an understanding of different types of LLMs and how they fit into RAG
Build a RAG application using a vector database and multiple embedders
Test different generators like GPT-4o, Claude, Command-R, and more
Build your own API for running RAG
Demonstrate a chat application based on your RAG work
Utilize advance dtechniques like GraphRAG
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