Building Real-World AI with RAG: A Hands-On Guide to Integrating Your Data with Large Language Models

By David S Richard

Building Real-World AI with RAG: A Hands-On Guide to Integrating Your Data with Large Language Models

Unlock the full potential of AI by mastering Retrieval-Augmented Generation (RAG)-the breakthrough approach that makes large language models smarter, more reliable, and tailored to your data.

This book is not just theory. It's a step-by-step, practical guide designed to help you move beyond basic AI experiments and start building real-world applications that deliver measurable results. Whether you're a developer, data professional, or tech leader, you'll learn exactly how to integrate your own datasets with today's most powerful language models to create AI solutions that are accurate, scalable, and business-ready.

Inside, you'll discover how to:

Set up and optimize RAG pipelines that connect your data with large language models.Harness vector databases and embeddings to supercharge search and retrieval.Overcome the limitations of generic AI models by grounding them in your organization's unique knowledge.Build hands-on projects that transform customer support, research, analytics, and more.

Instead of struggling with inconsistent AI outputs or wasting hours tweaking prompts, you'll gain a clear, actionable framework that turns advanced concepts into tools you can use immediately. Each chapter is packed with real examples, code snippets, and proven best practices to ensure you don't just understand RAG-you can put it into action from day one.

If you're serious about creating AI systems that actually work in the real world, this book is your essential blueprint. By the time you finish, you won't just know what Retrieval-Augmented Generation is-you'll know how to use it as the missing piece to make AI practical, powerful, and truly your own.

Take the guesswork out of AI. This is the guide that shows you how to build solutions that last.

• Format: Paperback
• Language: English
• ISBN: B0FQHQH7DC
• ISBN13: 9798264559372
• Release Date: September 2025
• Publisher: Independently Published
• Length: 140 Pages
• Weight: 0.45 lbs.
• Dimensions: 0.3" x 6.1" x 9.2"