RAG Mastery – Build Intelligent Search Systems: A Hands-On Guide to Retrieval-Augmented Generation with Python (The AI Masterclass Series) - Softcover

Gupta, Sankalp; PUBLICATIONS, TELI

Softcover

ISBN 13: 9798188979324

Publisher: Independently published, 2026

Synopsis

Build AI systems that answer with facts—not hallucinations.

Retrieval-Augmented Generation (RAG) has become the foundation of modern AI applications, powering intelligent assistants, enterprise search engines, document question-answering systems, customer support bots, legal research platforms, and knowledge management solutions.

RAG Mastery is a practical, code-first guide that teaches you how to design, build, optimize, and deploy production-ready Retrieval-Augmented Generation systems using Python and today's most powerful AI tools.

Instead of overwhelming you with theory, this book walks you through complete implementations with clear explanations, real-world projects, and fully working code.

Inside this book you'll learn how to:

† Understand the complete RAG architecture from indexing to answer generation

† Build semantic search systems using embeddings and vector databases

† Master LangChain for modern AI application development

† Work with Chroma, FAISS, Pinecone, and Weaviate

† Load PDFs, Word documents, web pages, databases, and enterprise data

† Design effective chunking strategies for maximum retrieval quality

† Implement hybrid search, reranking, metadata filtering, and advanced retrieval techniques

† Build conversational RAG with memory and context awareness

† Evaluate RAG systems using industry-standard metrics

† Optimize latency, accuracy, scalability, and production performance

† Deploy enterprise-grade RAG applications with confidence

Hands-on Projects Included

• Intelligent Document Question-Answering System

• Enterprise Knowledge Base Assistant

• Multi-Source AI Research Assistant

Every chapter includes practical examples, production-ready Python code, best practices, troubleshooting advice, architectural insights, and implementation techniques that can be immediately applied to real-world AI products.

Whether you're an AI engineer, Python developer, software architect, machine learning practitioner, data scientist, or computer science student, this book provides the skills needed to build reliable AI systems powered by Retrieval-Augmented Generation.

If you want to move beyond chatbots and create intelligent AI applications that retrieve accurate information, reduce hallucinations, and scale to enterprise workloads, RAG Mastery is your complete guide.

Edition details

• Publisher: Independently published
• Publication date: 2026
• Language: English
• ISBN 13: 9798188979324
• Binding: Paperback
• Number of pages: 281