treygrainger/ai-powered-search
The codebase for the book "AI-Powered Search" (Manning Publications, 2025)
This project provides practical code examples for building smarter search engines that continuously learn from user interactions and content. You'll put in user behavior data and your content, and get out a search engine that delivers more relevant, personalized results. It's for search engineers, data scientists, or developers responsible for improving search functionality in applications and websites.
372 stars.
Use this if you need to implement advanced, AI-driven features like semantic search, personalized results, or question answering into your existing search application.
Not ideal if you're looking for a fully-packaged, plug-and-play search solution rather than a collection of code examples and techniques for building one.
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372
Forks
98
Language
Jupyter Notebook
License
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Last pushed
Mar 06, 2026
Commits (30d)
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