Retrieval Augmented Generation (RAG)

Module Overview

In this module, you will learn:

  • What Retrieval Augmented Generation (RAG) is and how you can use it to improve GenerativeAI model responses.

  • How vectors and embeddings work, and how they can be used in RAG to find relevant information.

  • How to use a vector indexes in Neo4j and when they are useful for finding context for Generative AI applications.

  • About GraphRAG techniques, and how they can be used to enhance information retrieval.

If you are ready, let’s get going!

Ready? Let’s go →

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