02041nam a22002177a 4500 20260722143906.0 260722s2024 |||||||| |||| 00| 0 eng d 9781835887905 PK-LaUMT 006.3 BOU-U Bourne, Keith 14023 Unlocking data with generative AI and RAG : enhance generative AI systems by integrating internal data with large language models using RAG / Keith Bourne Birmingham : Packt Publishing, 2024 xxii, 323 p. Index present "Generative AI is helping organizations tap into their data in new ways, with retrieval-augmented generation (RAG) combining the strengths of large language models (LLMs) with internal data for more intelligent and relevant AI applications. The author harnesses his decade of ML experience in this book to equip you with the strategic insights and technical expertise needed when using RAG to drive transformative outcomes. The book explores RAG's role in enhancing organizational operations by blending theoretical foundations with practical techniques. You'll work with detailed coding examples using tools such as LangChain and Chroma's vector database to gain hands-on experience in integrating RAG into AI systems. The chapters contain real-world case studies and sample applications that highlight RAG's diverse use cases, from search engines to chatbots. You'll learn proven methods for managing vector databases, optimizing data retrieval, effective prompt engineering, and quatitatively evaluating performance. The book also takes you through advanced integrations of RAG with cutting-edge AI agents and emerging non-LLM technologies. By the end of this book, you'll be able to successfully deploy RAG in business settings, address common challenges, and push the boundaries of what's possible with this revolutionary AI technique"--Cover, page 4 Eng Generative-AI 9558 Large language models-AI 14024 BK 141574 141574 0 0 0 0 01 01 2026-07-22 0 006.3 BOU-U 153377 2026-07-22 14:39:17 2026-07-22 BK