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Register: https://www.meetup.com/bliss-speaker-series/events/308415769/

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) and GraphRAG and their role in ​- 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.

BLISS x Neo4j: Powering GenAI with Knowledge Graphs

In this hands-on workshop, you will learn how Knowledge Graphs and Retrieval Augmented Generation (RAG) can help GenAI projects avoid hallucination and provide access to reliable data. Topics include LLMs and hallucination, integrating knowledge graphs, GraphRAG, vector indexes and embeddings, querying graphs with natural language, and using Python and OpenAI to create GraphRAG retrievers and GenAI applications.

knowledge graphs retrieval augmented generation (rag) graphrag vector indexes embeddings Python openai
BLISS x Neo4j: Powering GenAI with Knowledge Graphs
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