click to view more

Retrieval-Augmented Generation (RAG) and Vector Databases: A Practical Guide for AI Developers

by Newton, Gus

$12.90

List Price: $16.00
Save: $3.10 (19%)
add to favourite
  • In Stock - Ship in 24 hours with Free Online tracking.
  • FREE DELIVERY by Tuesday, July 22, 2025
  • 24/24 Online
  • Yes High Speed
  • Yes Protection

Description

Retrieval-Augmented Generation (RAG) and Vector Databases: A Practical Guide for AI Developers

AI is only as powerful as the information it can access. Retrieval-Augmented Generation (RAG) bridges the gap between static language models and real-time knowledge retrieval, enabling AI to generate more accurate, context-aware responses. This book provides a hands-on, practical guide to building RAG-powered AI systems using vector databases for efficient and intelligent information retrieval.

From understanding how RAG improves AI responses to implementing scalable retrieval systems, this book walks you through step-by-step tutorials, real-world applications, and best practices for optimization. Whether you're developing AI-powered search engines, chatbots, or enterprise knowledge systems, this guide equips you with the skills to build robust retrieval-enhanced AI models.

This book takes a deep dive into RAG and vector search, covering:

  • How RAG enhances AI models by retrieving relevant context before generating responses.
  • Vector databases (FAISS, Pinecone, Weaviate, and more) and their role in AI-powered search.
  • Step-by-step implementation of RAG pipelines using Python and modern frameworks like LangChain and Haystack.
  • Optimizing retrieval performance to improve accuracy, reduce latency, and scale AI systems.
  • Real-world use cases in enterprise search, personalized recommendations, chatbots, healthcare, finance, and cybersecurity.

By the end of this book, you'll have the practical knowledge to build, deploy, and scale RAG-based applications.

Key Features of This Book

Comprehensive coverage of RAG, vector databases, and retrieval techniques.
Practical tutorials and hands-on code examples using Python.
Real-world applications for enterprise AI, e-commerce, and search engines.
Step-by-step guidance on optimizing retrieval and reducing AI hallucinations.
Deployment strategies for scaling RAG pipelines in cloud and on-premise environments.

This book is perfect for:

  • AI developers and data scientists building retrieval-augmented AI systems.
  • Machine learning engineers optimizing search and retrieval models.
  • Software developers working on chatbots, virtual assistants, and AI-powered search.
  • AI researchers and enthusiasts interested in RAG, vector search, and LLMs.

Unlock the full potential of AI-powered retrieval with Retrieval-Augmented Generation and Vector Databases! Whether you're a beginner or an experienced AI professional, this book will equip you with the skills to build advanced, intelligent systems. Get your copy today and start building RAG-powered AI applications that deliver smarter, more accurate responses.

Last updated on

Product Details

  • Mar 20, 2025 Pub Date:
  • 9798314910122 ISBN-10:
  • 9798314910122 ISBN-13:
  • English Language