BLISS x Neo4j: Hands-On with GraphRAG - Powering GenAI with Knowledge Graphs
Abstract
Generative AI models have the potential to increase productivity and provide access to data, but they need good context to be truly useful.
In this hands-on workshop, you will learn how Knowledge Graphs and Retrieval Augmented Generation (RAG) can help your GenAI projects avoid hallucination and provide access to reliable data.
In this hands-on workshop, you will:
Learn about Large Language Models (LLMs), hallucination and integrating knowledge graphs
Explore Retrieval Augmented Generation (RAG)
Use vector indexes and embeddings to find similar data
Query graphs using natural language
Use Python and OpenAI to create GraphRAG retrievers and GenAI applications
This workshop will put you on the path to controlling Generative AI applications and integrating them into your projects.
Logistics
The workshop will be delivered using Neo4j's GraphAcademy platform, learners will only need a laptop and an internet connection. Everything else will be provided.
The only prerequisite for this workshop is a knowledge of Python and being capable of reading simple programs.
About the speaker
Martin is an experienced computer science educator and open source software developer.
Martin creates educational content for Neo4j and supports developers in using graph technology to understand their data.
As a child he wanted to be either a Computer Scientist, Astronaut or Snowboard Instructor.