Vector Search with JavaScript (Pragmatic Bookshelf)

PragmaticBookshelf

PragmaticBookshelf

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Cut through the complexity and apply AI-driven vector search strategies to deliver smarter, more intuitive search experiences that keep users engaged.

Ben Greenberg @hummusonrails

edited by Susannah Davidson @susannahd

Make search results smarter and more useful for everyday users and deliver more relevant results with vector search. Go beyond keyword matching to build search experiences that understand meaning, context, and similarity. Use AI-powered techniques to create recommendation systems, personalized search, and content discovery tools. Implement vector search from the ground up with step-by-step guidance, real-world examples, and hands-on coding. Generate embeddings, construct vector indexes, and optimize search accuracy with practical methods that integrate seamlessly into JavaScript applications. Whether refining an existing project or developing a new one, unlock the power of AI-driven search to create smarter, more intuitive user experiences.

Stop relying on outdated search methods. Deploy vector search and deliver smarter, more intuitive search experiences that keep users engaged. This comprehensive guide takes a deep dive into the world of vector search, offering a hands-on approach for developers looking to bring AI-powered utility and precision into their projects. This book demystifies the core concepts of vector search, making them accessible and practical — and you don’t need a background in math to learn vector search techniques!

Revolutionize search with AI-powered techniques that go beyond simple keyword matching. Implement vector search to build applications that understand intent, meaning, and similarity. Generate embeddings, construct efficient vector indexes, and power recommendation systems, personalized search, and content discovery tools. Master practical techniques to integrate vector search into JavaScript applications with real-world examples and step-by-step tutorials.

Cut through the complexity and apply AI-driven search strategies to create better user experiences. Use vector search to return more relevant results, surface hidden insights, and handle ambiguous queries with greater precision. Build scalable, high-performance search systems that enhance products across industries, from e-commerce and media to finance and healthcare.


Ben Greenberg is a developer advocate and software engineer who is passionate about making complex tech accessible. He has worked with New Relic, Vonage, and Couchbase, and currently serves on the board of Ruby Central. A frequent speaker and instructor at global conferences, Ben shares insights and resources at bengreenberg.dev.


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