RAG 2.0 in Action
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Home > Computing and Information Technology > Computer science > Artificial intelligence > Neural networks and fuzzy systems > RAG 2.0 in Action: A Hands-On Guide to Building Next-Level Retrieval-Augmented AI Systems
RAG 2.0 in Action: A Hands-On Guide to Building Next-Level Retrieval-Augmented AI Systems

RAG 2.0 in Action: A Hands-On Guide to Building Next-Level Retrieval-Augmented AI Systems


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About the Book

The era of static AI models is over. The future belongs to Retrieval-Augmented Generation (RAG) - systems that learn continuously, retrieve context dynamically, and generate knowledge with precision. RAG 2.0 in Action is the definitive developer's guide to designing and deploying next-generation RAG pipelines - the foundation of intelligent, context-aware AI. Moving far beyond the basics of embedding and retrieval, this hands-on book teaches you how to build scalable, production-ready retrieval-augmented systems using today's leading frameworks, including LangChain, LlamaIndex, and LangGraph. Through clear explanations and step-by-step projects, you'll master every stage of the modern RAG lifecycle - from data ingestion, indexing, and hybrid retrieval to context management, generation fidelity, and continuous learning loops. Real-world case studies show how RAG 2.0 powers enterprise-grade assistants, research copilots, and multi-agent knowledge systems across domains like finance, healthcare, and engineering. You'll learn how to: Architect retrieval-aware pipelines that outperform standard LLMs. Combine dense, sparse, and multi-vector embeddings for richer context. Implement Graph RAG, memory-augmented reasoning, and agentic retrieval loops. Optimize for latency, cost, and factual accuracy in production environments. Prepare for the future - RAG 3.0 and continuous knowledge ecosystems. Every concept is explained in plain English, reinforced by practical code you can run immediately. Whether you're a developer, ML engineer, or system architect, this book gives you the framework, mindset, and toolkit to build retrieval-driven intelligence that scales. Hands-on. Forward-looking. Production-ready. This is not just a book about RAG - it's your roadmap to building the intelligent systems that will define the next era of AI. Perfect for: Developers - Machine-Learning Engineers - AI Researchers - System Architects - Technical Leaders exploring enterprise-level AI augmentation.


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Product Details
  • ISBN-13: 9798274424356
  • Publisher: Independently Published
  • Publisher Imprint: Independently Published
  • Height: 254 mm
  • No of Pages: 320
  • Returnable: N
  • Sub Title: A Hands-On Guide to Building Next-Level Retrieval-Augmented AI Systems
  • Width: 178 mm
  • ISBN-10: 8274424352
  • Publisher Date: 13 Nov 2025
  • Binding: Paperback
  • Language: English
  • Returnable: N
  • Spine Width: 17 mm
  • Weight: 607 gr


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