Enhancing AI Similarity Searches with MongoDB скачать в хорошем качестве

Enhancing AI Similarity Searches with MongoDB

Welcome to Episode 4 of the Bill's Guide to A.I. series! In this episode, Bill Kennedy explores how to leverage MongoDB's vector database capabilities to enhance similarity searches. Bill walks through setting up MongoDB Atlas, explaining how to create collections and indexes to store vectorized data and conduct similarity searches using cosine similarity, making this an essential tool for real-world AI applications. Bill demonstrates the process of connecting to MongoDB, creating a vector index, and performing a vector search with a simple four-point vector embedding. He highlights the importance of using vector databases like MongoDB for fast and efficient similarity searches, especially when working with large language models (LLMs) to handle real-world data. Bill also touches on using Docker to set up the MongoDB environment and offers insight into how indexes ensure accurate search results in vector databases. If you're looking to expand your knowledge of AI and learn how to implement vector databases in your AI projects, this episode provides the foundational skills you need to integrate MongoDB and LLMs for efficient, real-world applications. Things you will learn in this video: Vector Database Setup: Learn how to set up MongoDB Atlas for vector search. Indexing and Searching: Discover how to create vector indexes and perform efficient searches. Cosine Similarity: Understand how MongoDB uses cosine similarity to match vectorized data. Comment below or tweet us on twitter & let us know your thoughts, we want to hear from you! ~ If you found this video helpful, hit that like button & subscribe for more content like this. ---- Access our online courses → https://www.ardanlabs.com/education/ Attending a live training → https://www.ardanlabs.com/live-traini... Other Links: Website: https://www.ardanlabs.com/ Github: https://github.com/ardanlabs Twitter:   / ardanlabs   #A.I #programming #education #tutorials #tips