10-19, 13:30–15:30 (Europe/Lisbon), Workshops 1
In this GenAI workshop, you will learn how Knowledge Graphs and Retrieval Augmented Generation (RAG) can support your GenAI projects.
In this GenAI workshop, you will learn how Knowledge Graphs and Retrieval Augmented Generation (RAG) can support your GenAI projects.
You will:
Use Vector indexes and embeddings in Neo4j to perform similarity and keyword search
Use Python, LangChain and OpenAI to create a Knowledge Graph of unstructured data
Learn about Large Language Models (LLMs), hallucination and integrating knowledge graphs
Explore Retrieval Augmented Generation (RAG) and its role in grounding LLM-generated content
After completing this workshop, you will be able to explain the terms LLM, RAG, grounding, and knowledge graphs. You will also have the knowledge and skills to create simple LLM-based applications using Neo4j and Python.
This workshop will put you on the path to controlling LLMs and enabling their integration into your projects.
Beginner
What are the main topics of your talk? –GenAI, Knowledge Graph, Langchain, Vectors
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.