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Handbook of Retrieval Augmented Generation: Building Context-Enriched AI Systems - Couverture souple
Synopsis
Unlock the power of next-generation AI with the Handbook of Retrieval-Augmented Generation, a comprehensive guide designed for AI practitioners, researchers, and technology leaders. This essential volume explores the cutting-edge paradigm that combines powerful large language models with smart knowledge retrieval to produce highly accurate, context-aware, and reliable AI solutions.
Inside this handbook, you will discover:
Foundational principles of Retrieval-Augmented Generation (RAG), including semantic embeddings, vector search, and prompt engineering
Step-by-step guidance on building scalable, efficient RAG pipelines from data preparation to deployment
Methods for managing multi-turn conversations and integrating multi-modal data (text, images, audio, and video)
Detailed exploration of domain-specific adaptations tailored for healthcare, finance, legal, and education sectors
Insights into evaluating RAG systems end-to-end, monitoring live deployments, and establishing continuous feedback loops
Advanced strategies for scaling, personalization, reinforcement learning integration, and long-term memory architectures
Real-world case studies from enterprise deployments and academic research showcasing practical applications and outcomes
Written with a practical focus, this book balances rigorous technical depth with accessible explanations, making it ideal for professionals aiming to implement RAG systems as well as academics exploring future AI research directions.
Whether you are developing intelligent chatbots, AI-driven knowledge assistants, or personalized learning systems, this handbook will empower you with the tools and insights needed to create trustworthy, high-performance, context-enriched AI applications.
Key Features:
Comprehensive coverage of RAG theory, technology, and practice
Practical implementation guidance leveraging popular open-source tools and cloud services
Real-world examples and case studies illustrating impact across industries
Future-facing insights on AI evolution, multi-modal integration, and autonomous AI agents
Elevate your AI capabilities today by mastering the art and science of Retrieval-Augmented Generation with this definitive resource.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
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Handbook of Retrieval Augmented Generation (Paperback)
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Paperback. Etat : new. Paperback. Unlock the power of next-generation AI with the Handbook of Retrieval-Augmented Generation, a comprehensive guide designed for AI practitioners, researchers, and technology leaders. This essential volume explores the cutting-edge paradigm that combines powerful large language models with smart knowledge retrieval to produce highly accurate, context-aware, and reliable AI solutions.Inside this handbook, you will discover: Foundational principles of Retrieval-Augmented Generation (RAG), including semantic embeddings, vector search, and prompt engineeringStep-by-step guidance on building scalable, efficient RAG pipelines from data preparation to deploymentMethods for managing multi-turn conversations and integrating multi-modal data (text, images, audio, and video)Detailed exploration of domain-specific adaptations tailored for healthcare, finance, legal, and education sectorsInsights into evaluating RAG systems end-to-end, monitoring live deployments, and establishing continuous feedback loopsAdvanced strategies for scaling, personalization, reinforcement learning integration, and long-term memory architecturesReal-world case studies from enterprise deployments and academic research showcasing practical applications and outcomesWritten with a practical focus, this book balances rigorous technical depth with accessible explanations, making it ideal for professionals aiming to implement RAG systems as well as academics exploring future AI research directions.Whether you are developing intelligent chatbots, AI-driven knowledge assistants, or personalized learning systems, this handbook will empower you with the tools and insights needed to create trustworthy, high-performance, context-enriched AI applications.Key Features: Comprehensive coverage of RAG theory, technology, and practicePractical implementation guidance leveraging popular open-source tools and cloud servicesReal-world examples and case studies illustrating impact across industriesFuture-facing insights on AI evolution, multi-modal integration, and autonomous AI agentsElevate your AI capabilities today by mastering the art and science of Retrieval-Augmented Generation with this definitive resource. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N° de réf. du vendeur 9798265888914
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Paperback. Etat : new. Paperback. Unlock the power of next-generation AI with the Handbook of Retrieval-Augmented Generation, a comprehensive guide designed for AI practitioners, researchers, and technology leaders. This essential volume explores the cutting-edge paradigm that combines powerful large language models with smart knowledge retrieval to produce highly accurate, context-aware, and reliable AI solutions.Inside this handbook, you will discover: Foundational principles of Retrieval-Augmented Generation (RAG), including semantic embeddings, vector search, and prompt engineeringStep-by-step guidance on building scalable, efficient RAG pipelines from data preparation to deploymentMethods for managing multi-turn conversations and integrating multi-modal data (text, images, audio, and video)Detailed exploration of domain-specific adaptations tailored for healthcare, finance, legal, and education sectorsInsights into evaluating RAG systems end-to-end, monitoring live deployments, and establishing continuous feedback loopsAdvanced strategies for scaling, personalization, reinforcement learning integration, and long-term memory architecturesReal-world case studies from enterprise deployments and academic research showcasing practical applications and outcomesWritten with a practical focus, this book balances rigorous technical depth with accessible explanations, making it ideal for professionals aiming to implement RAG systems as well as academics exploring future AI research directions.Whether you are developing intelligent chatbots, AI-driven knowledge assistants, or personalized learning systems, this handbook will empower you with the tools and insights needed to create trustworthy, high-performance, context-enriched AI applications.Key Features: Comprehensive coverage of RAG theory, technology, and practicePractical implementation guidance leveraging popular open-source tools and cloud servicesReal-world examples and case studies illustrating impact across industriesFuture-facing insights on AI evolution, multi-modal integration, and autonomous AI agentsElevate your AI capabilities today by mastering the art and science of Retrieval-Augmented Generation with this definitive resource. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. N° de réf. du vendeur 9798265888914
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