Mastering RAG for AI: Build Scalable, High-Performance Knowledge Applications

By Fredrick B Forest

Mastering RAG for AI: Build Scalable, High-Performance Knowledge Applications is your definitive guide to harnessing the power of Retrieval-Augmented Generation (RAG) - the cutting-edge technique revolutionizing modern AI systems.

Whether you're a machine learning engineer, data scientist, or software architect, this book equips you with the tools and knowledge to design and deploy scalable, high-performance AI applications that integrate vast knowledge sources in real time.

Starting from the foundational concepts of RAG, you'll explore practical architectures that combine large language models (LLMs) with intelligent retrieval systems. Through hands-on examples and production-ready strategies, you'll learn how to:

Understand the core principles and components of RAG pipelinesOptimize vector databases and embedding strategies for accurate retrievalFine-tune LLMs for domain-specific applicationsEnsure scalability, latency reduction, and real-time performanceImplement RAG in knowledge-intensive systems like chatbots, search engines, and enterprise assistantsAddress key challenges such as hallucinations, evaluation metrics, and cost efficiency

Packed with real-world case studies and best practices, Mastering RAG for AI empowers you to build intelligent systems that don't just generate - they understand, retrieve, and reason.

• Format: Paperback
• Language: English
• ISBN: B0FF8X7CM2
• ISBN13: 9798289317414
• Release Date: June 2025
• Publisher: Independently Published
• Length: 126 Pages
• Weight: 0.41 lbs.
• Dimensions: 0.3" x 6.1" x 9.2"