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Carte VECTOR DATABASE & RAG ENGINEERING FINN CORDEX

VECTOR DATABASE & RAG ENGINEERING

DESIGNING SCALABLE, LOW-LATENCY RETRIEVAL SYSTEMS FOR LLMS, AI AGENTS, AND PRODUCTION APPLICATIONS

Autor: FINN CORDEX
Limbă: engleză
Legare: Carte broșată
Editura: Independently published
Disponibilitate: În depozitul extern
Expediem în 9-15 zile
87.97 lei
Unlock the full power of Large Language Models (LLMs), AI agents, and production-grade AI applicatio...

Informații despre carte

Autor
FINN CORDEX
Limbă
engleză
Legare
Carte - Carte broșată
Publicat
2025
Pagini
172
EAN
9798261952480
Enbook ID
50514574
Editura
Independently published
Greutate
208
Dimensiuni
140 x 216 x 9

Descriere completă

Unlock the full power of Large Language Models (LLMs), AI agents, and production-grade AI applications with Vector Database & RAG Engineering. This advanced guide equips developers, ML engineers, and data scientists with the expertise to design scalable, low-latency retrieval systems that power modern AI workflows.

Inside, you'll discover:

  • How vector databases underpin retrieval-augmented generation (RAG) and real-time AI reasoning.

  • Step-by-step architectural patterns for building high-performance, production-ready retrieval systems.

  • Expert insights into embedding strategies, indexing, graph orchestration, and memory management.

  • Hands-on, production-aware Python examples with LangChain and LangGraph, taking you from minimal prototypes to enterprise-ready deployments.

  • Techniques for optimization, testing, debugging, and secure AI deployment, including considerations for GDPR and data governance.

Whether you're designing intelligent assistants, multimodal search engines, or agentic automation pipelines, this book bridges theory and practice, giving you actionable frameworks and expert best practices that go far beyond tutorials.

Transform your AI projects with systems that are robust, efficient, and ready for real-world scale-all guided by a seasoned AI engineer and technical author with 10+ years of applied experience.

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