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Retrieval-Augmented Generation (RAG): The Complete Practical Guide to Building Smarter AI with Knowledge, Search, and Large Language Models

by Logan Trent Wilder
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Current price ₹1,460.00
Original price ₹1,612.00
Original price ₹1,612.00
Original price ₹1,612.00
(-9%)
₹1,460.00
Current price ₹1,460.00

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Book cover type: Paperback
  • ISBN13: 9798269815312
  • Binding: Paperback
  • Subject: N/A
  • Publisher: Independently Published
  • Publisher Imprint: Independently Published
  • Publication Date:
  • Pages: 134
  • Original Price: GBP 12.74
  • Language: English
  • Edition: N/A
  • Item Weight: 327 grams
  • BISAC Subject(s): Artificial Intelligence / Generative AI

Book Description

Unlock the power of Retrieval-Augmented Generation (RAG) - the groundbreaking fusion of knowledge, search, and large language models that's redefining the future of artificial intelligence.

In an era where data and intelligence must work hand in hand, Retrieval-Augmented Generation (RAG) empowers AI systems to move beyond static memory and into dynamic reasoning. This comprehensive guide walks you through everything you need to master RAG - from core theory to real-world applications - helping you build smarter, context-aware, and more trustworthy AI solutions.


What You'll Learn
  • Understand RAG from the ground up - grasp how retrieval and generation work together to enhance large language models (LLMs).

  • Master practical implementation - set up your environment, build pipelines, and integrate tools like LangChain, LlamaIndex, and Haystack.

  • Optimize performance - learn embedding strategies, hybrid retrieval techniques, and fine-tuning methods that boost precision and relevance.

  • Explore advanced topics - dive into multimodal RAG, AI agents, autonomous workflows, and cross-domain retrieval systems.

  • Apply real-world use cases - build healthcare, finance, education, and enterprise RAG systems using practical, step-by-step examples.


Who This Book Is For
  • AI Developers & Engineers - who want to build intelligent, knowledge-aware applications.

  • Data Scientists & Researchers - seeking to integrate retrieval-based reasoning into existing LLM systems.

  • Students & Enthusiasts - looking to learn RAG concepts from beginner to advanced levels with clarity and structure.

  • Tech Innovators & Startups - exploring how to leverage RAG for real-world business solutions and automation.


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