Open Daily: 10am - 10pm | Alley door pickup 10am - 7pm 3038 Hennepin Ave Minneapolis, MN
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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Build an Advanced Rag Application (from Scratch)

Build an Advanced Rag Application (from Scratch)

Farooq, Hamza

Paperback

Series: From Scratch

General Computers

PREORDER - Expected ship date December 29, 2026

ISBN10: 1633436527
ISBN13: 9781633436527
Publisher: Manning Publications
Published: Dec 29 2026
Pages: 325
Weight: 0.85
Language: English
Get the eBook free when you register your print book at Manning.

Retrieval Augmented Generation--RAG--is now the standard way to improve LLM accuracy and relevance. But building production-grade RAG systems requires far more than connecting an LLM to a vector database. In this book, you'll learn RAG from first principles by creating a complete portfolio of end-to-end applications. You'll build each component of the pipeline, ensuring full control over every part of the stack.

Written by former Google research scientist Hamza Farooq, this hands-on guide takes you from LLM and transformer fundamentals through keyword search and semantic retrieval to production RAG systems. You'll build a hotel search engine with semantic ranking, implement semantic caching for cost-effective production deployments, develop autonomous AI agents powered by RAG context, and deploy optimized open-source LLMs. Through under-the-hood experience, you'll master embeddings, chunking, reranking, vector databases, evaluation frameworks, fine-tuning, and more.

What's inside

- Design and implement efficient search algorithms for LLM applications

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