{"repo":"treygrainger/ai-powered-search","free":true,"listed":false,"github":"https://github.com/treygrainger/ai-powered-search","clone":"git clone https://github.com/treygrainger/ai-powered-search.git","description":"The codebase for the book \"AI-Powered Search\" (Manning Publications, 2025) and associated \"AI-Powered Search: Modern Retrieval for Humans & Agents\" Maven course","language":"Jupyter Notebook","stars":403,"topics":["ai","ai-powered-search","foundation-models","generative-search","hybrid-search","information-retrieval","large-language-models","learning-to-rank","multimodal-search","opensearch"],"license":null,"category":"machine-learning","readme_excerpt":"AI-Powered Search Code examples for the book AI-Powered Search by Trey Grainger, Doug Turnbull, and Max Irwin. Published by Manning Publications. Book Overview AI-Powered Search teaches you the latest machine learning techniques to build search engines that continuously learn from your users and your content to drive more domain-aware and intelligent search. Search engine technology is rapidly evolving, with Artificial Intelligence (AI) driving much of that innovation. Crowdsourced relevance and the integration of large language models (LLMs) like GPT and other foundation models are massively accelerating the capabilities and expectations of search technology. AI-Powered Search will teach you modern, data-science-driven search techniques like: - Semantic search using dense vector embeddings from foundation models - Retrieval Augmented Generation - Question answering and summarization combining search and LLMs - Fine-tuning transformer-based LLMs - Personalized search based on user signals and vector embeddings - Collecting user behavioral signals and building signals boosting models - Semantic knowledge graphs for domain-specific learning - Implementing machine-learned ranking models (learning to rank) - Building click models to automate machine-learned ranking - Generative search, hybrid search, and the search frontier Today’s search engines are expected to be smart, understanding the nuances of natural language queries, as well as each user’s preferences and context. This b","default_branch":null,"files":null,"tree":[],"storefront":"/r/treygrainger","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/treygrainger/ai-powered-search/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}