May 31, 2026
Hands – On RAG for Production Design, Develop, and Deploy Production – Ready RAG Applications (Tr…
HandOn RAG for Production Design, Develop, and Deploy Production – Ready RAG Applications (True Retail ) | 5.23 MB
Title: Hands-On RAG for Production
Author: Ofer Mendelevitch
Category: Nonfiction, Computers, Advanced Computing, Natural Language Processing, Engineering, Computer Architecture, General Computing
Language: English | 358 Pages | ISBN: 9798341621688
Description:
Retrieval-augmented generation (RAG) is the go-to strategy for integrating large language models with your organization’s unique knowledge. However, the market is full of RAG pipelines and components, making it hard to choose the right solution for your enterprise’s needs. This book simplifies the process, offering a comprehensive road map to building, refining, and scaling production-grade RAG applications.
Authors Ofer Mendelevitch and Forrest Bao guide you through every phase of development, from data ingestion, embeddings, and vector search to advanced techniques like agentic RAG, multimodal RAG, and GraphRAG. Engineers and architects will learn how to tackle the challenges they’ll encounter when building RAG applications at enterprise scale: ensuring high accuracy with minimal hallucinations, maintaining low-latency performance, safeguarding data privacy, and providing transparent, explainable responses among them.Determine whether to build RAG yourself…
Retrieval-augmented generation (RAG) is the go-to strategy for integrating large language models with your organization’s unique knowledge. However, the market is full of RAG pipelines and components, making it hard to choose the right solution for your enterprise’s needs. This book simplifies the process, offering a comprehensive road map to building, refining, and scaling production-grade RAG applications.
Authors Ofer Mendelevitch and Forrest Bao guide you through every phase of development, from data ingestion, embeddings, and vector search to advanced techniques like agentic RAG, multimodal RAG, and GraphRAG. Engineers and architects will learn how to tackle the challenges they’ll encounter when building RAG applications at enterprise scale: ensuring high accuracy with minimal hallucinations, maintaining low-latency performance, safeguarding data privacy, and providing transparent, explainable responses among them.
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