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Unlocking Data with Generative AI and RAG. Learn the fundamentals and build Agents with RAG-powered memory, GraphRAG, and intelligent recall - Second Edition Keith Bourne

Język publikacji: angielski
Unlocking Data with Generative AI and RAG. Learn the fundamentals and build Agents with RAG-powered memory, GraphRAG, and intelligent recall - Second Edition Keith Bourne - okladka książki

Unlocking Data with Generative AI and RAG. Learn the fundamentals and build Agents with RAG-powered memory, GraphRAG, and intelligent recall - Second Edition Keith Bourne - okladka książki

Autor:
Keith Bourne
Serie wydawnicze:
Hands-on
Ocena:
Developing AI agents that remember, adapt, and reason over complex knowledge is no longer a distant goal- it’s now possible with Retrieval-Augmented Generation (RAG). This second edition of the bestselling guide expands into the future of agentic systems, showing how to build intelligent, explainable, and context-aware applications powered by RAG pipelines.
You’ll explore the building blocks of agentic memory, including semantic caches, procedural learning via LangMem, and the emerging CoALA framework for cognitive agents. You’ll also learn to integrate GraphRAG with tools like Neo4j to create deeply contextualized AI responses grounded in ontology-driven data.
This book walks you through real implementations of working, episodic, semantic, and procedural memory using vector stores, prompting strategies, and feedback loops. With hands-on code and production-ready patterns, you’ll gain the skills to build advanced AI systems that don’t just generate answers- they learn, recall, and evolve.
Written by a seasoned AI educator and engineer, this book blends theoretical clarity with deep practical insight, offering both foundational knowledge and cutting-edge tools for modern AI development.

O autorze książki

Keith is a Senior Generative AI Data Scientist at Johnson & Johnson, leveraging his decade of experience in machine learning. With an MBA from Babson College and a Master of Applied Data Science from the University of Michigan, Keith has made significant contributions to healthcare innovation through his expertise in generative AI, particularly in developing a sophisticated generative AI platform incorporating Retrieval-Augmented Generation (RAG) and other advanced techniques. Keith has worked with a diverse set of clients including University of Michigan Healthcare, NFL, NOAA, Weather Channel, Becton Dickinson, Toyota, and Little Caesars.
Originally from Chagrin Falls, OH, Keith resides in Ann Arbor, MI with his wife and three daughters.

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