The AI Engineering Bible : Guide complet pour construire, déployer et scaler des systèmes IA - Thomas R. Caldwell - Marjane Mall - Image 1
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The AI Engineering Bible : Guide complet pour construire, déployer et scaler des systèmes IA - Thomas R. Caldwell

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Vendu par HEAVENBOOKS.MA

Découvrez "The AI Engineering Bible", le guide de référence écrit par Thomas R. Caldwell pour les ingénieurs, architectes et responsables techniques souhaitant maîtriser le cycle de vie complet des systèmes d'intelligence artificielle. Cet ouvrage de 284 pages propose une approche systématique et pratique pour passer de la conception à la mise en p...

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Description produit

Marque
GENERIC
Titre principal
The AI Engineering Bible: The Complete and Up-to-Date Guide to Build, Deploy and Scale Production Ready AI Systems
Editeur
Independently published
Type de produit
Paperback
Présentation du livre
Paperback
Release date
2/20/2026 12:00:00 AM
Langue d'origine
English
ISBN
2299725040
Dimensions
8.5 x 0.64 x 11 inches
Nombre de pages de livre
284 pages
Langue - Librairie
English
Résumé
A Comprehensive, Practical Guide to Building, Deploying, and Scaling Real-World AI SystemsWhile AI dominates headlines, most organizations face a different reality: stalled projects, fragile infrastructure, costly deployments, and no clear framework for building scalable, reliable systems.The AI Engineering Bible addresses this gap directly.Written for engineers, technical leads, AI architects, and product owners, this book offers a clear, systematic approach to building production-ready AI systems—grounded in current best practices, scalable infrastructure, and real-world application.Spanning every stage of the AI lifecycle—from problem definition and data acquisition to deployment, optimization, and long-term maintenance—it provides the structure and technical depth professionals need to confidently lead AI initiatives at scale.With this all-in-one guide in your hands, you will:Start by defining the problem and planning your AI system with precision—from aligning goals with business outcomes to structuring architecture, data strategy, ethics, compliance, and human-AI interaction from day oneBuild each layer of your system with reliability in mind, including data pipelines, preprocessing workflows, training loops, orchestration tools, and model selection—ready for integration into real-world software environmentsDeploy your AI models into production with confidence, using containerized services, scalable cloud infrastructure, secure API integrations, and version-controlled workflows that reduce downtime and riskExpand your system to handle increasing scale, applying proven strategies for distributed inference, federated learning, pipeline throughput, and load balancing—ensuring your architecture grows without bottlenecksOptimize performance across every dimension, from latency and throughput to memory usage and cost-efficiency, using cutting-edge techniques in tuning, compression, quantization, and system profilingEnsure long-term reliability and adaptability throu
Auteur(s)
Thomas R. Caldwell
Date de parution
2/20/2026 12:00:00 AM