Vector Search RAG Tutorial – Combine Your Data with LLMs with Advanced Search

Explore vector search and embeddings to seamlessly integrate your data with large language models like GPT-4 in this comprehensive tutorial. Begin with foundational concepts before diving into three hands-on projects: creating a semantic search for a movie database, implementing RAG with Atlas Vector Search, LangChain, and OpenAI, and developing a chatbot connected to your documentation. Gain practical experience using MongoDB Atlas for vector search and learn how to leverage these powerful tools to enhance your data-driven applications.

⌨️ Introduction
⌨️ What are vector embeddings?
⌨️ What is vector search?
⌨️ MongoDB Atlas vector search
⌨️ Project 1: Semantic search for movie database
⌨️ Project 2: RAG with Atlas Vector Search, LangChain, OpenAI
⌨️ Project 3: Chatbot connected to your documentation