RETRIEVAL-AUGMENTED GENERATION MASTERY / Najlacnejšie knihy
RETRIEVAL-AUGMENTED GENERATION MASTERY

Kód: 50596970

RETRIEVAL-AUGMENTED GENERATION MASTERY

Autor FINN CORDEX

Unleash the Power of Retrieval-Augmented Generation and Build Smarter, Scalable, and Production-Ready AI Systems.The age of static language models is over. In 2026, the future belongs to Retrieval-Augmented Generation (RAG) - a re ... celý popis

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Anotácia knihy

Unleash the Power of Retrieval-Augmented Generation and Build Smarter, Scalable, and Production-Ready AI Systems.

The age of static language models is over. In 2026, the future belongs to Retrieval-Augmented Generation (RAG) - a revolutionary paradigm that blends large language models (LLMs) with real-time, knowledge-retrieval pipelines to create intelligent, context-aware AI applications that truly understand your data.

In Retrieval-Augmented Generation Mastery (2026 Edition), acclaimed AI engineer and author Finn Cordex delivers the definitive guide for developers, ML engineers, and AI practitioners who want to master the art and engineering of RAG systems - from theory to real-world deployment.

Whether you're building internal knowledge assistants, enterprise search bots, or data-driven GenAI apps, this book equips you with everything you need to go from concept to production-ready intelligence.


What You'll Learn
Inside the Book

Structured for professional clarity and depth, this edition includes:


Who This Book Is For

This is not another surface-level AI tutorial. It's a masterclass for serious builders - developers, engineers, data scientists, and researchers who want to go beyond chatbots and understand how modern AI systems retrieve, reason, and respond with precision.

If you're ready to build intelligent systems that learn from your data, not just memorize it, this book will show you how - step by step, code by code.


Why This Edition Matters

Written for the rapidly evolving 2026 landscape, this updated edition reflects the latest breakthroughs in:

No shortcuts. No outdated theory. Just practical, battle-tested knowledge for modern AI engineers.

Master the framework that defines the next generation of AI.
Master Retrieval-Augmented Generation.

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