In this hands-on guide, author Nitin Borwankar takes you through the "why, what, and how" of vector databases, starting with the basic theory behind vector embeddings and progressing to building applications with real-world tools. You'll learn about Word2vec, how to convert open source SQL databases like SQLite3 and PostgreSQL into vector databases, and integrate them into retrieval-augmented generation (RAG) applications. Whether you're a Python developer, data engineer, or ML practitioner, this book gives you the foundation to leverage vector databases confidently in your AI projects. Understand the connection between vector databases, embeddings, and LLMs Learn practical approaches for transforming SQL databases into vector databases Build RAG applications for both personal and enterprise use Apply vector databases to solve real-world AI challenges Learn how to use vector databases with LLMs to build applications