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AI Infrastructure Engineering: Building GPU Systems, Optimizing Inference, Designing Distributed Architectures, and Running Production Deployments - Tapa blanda
Sinopsis
Reactive Publishing
Master the full stack of modern AI infrastructure, from raw hardware to large-scale production systems.
This practical guide delivers the essential knowledge and techniques used by today’s AI infrastructure engineers and platform teams. You will learn how to design, build, optimize, and operate reliable GPU-powered systems that power real-world AI workloads at scale.
Inside the book:
- Architect and deploy high-performance GPU clusters
- Optimize inference pipelines for speed, cost, and efficiency
- Design and manage distributed training and serving architectures
- Implement production-grade monitoring, scaling, and reliability practices
- Navigate the trade-offs between on-prem, cloud, and hybrid environments
Written for engineers, architects, and technical leaders, this book bridges the gap between theoretical machine learning and the complex realities of running AI in production. Whether you are building your first GPU cluster or scaling an existing platform to thousands of accelerators, you will find actionable strategies and battle-tested patterns you can apply immediately.
Clear, up-to-date, and focused on real engineering challenges, not hype.
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AI Infrastructure Engineering: Building GPU Systems, Optimizing Inference, Designing Distributed Architectures, and Running Production Deployments
Impresión bajo demandaLibrería: California Books, Miami, FL, Estados Unidos de America
Calificación del vendedor: 5 de 5 estrellas
Condición: New. Print on Demand. Nº de ref. del artículo: I-9798197947581
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EUR 36,00
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AI Infrastructure Engineering
Librería: Rarewaves.com USA, London, LONDO, Reino Unido
Calificación del vendedor: 5 de 5 estrellas
Paperback. Condición: New. Nº de ref. del artículo: LU-9798197947581
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AI Infrastructure Engineering (Paperback)
Impresión bajo demandaLibrería: Grand Eagle Retail, Bensenville, IL, Estados Unidos de America
Calificación del vendedor: 5 de 5 estrellas
Paperback. Condición: new. Paperback. Reactive PublishingMaster the full stack of modern AI infrastructure, from raw hardware to large-scale production systems.This practical guide delivers the essential knowledge and techniques used by today's AI infrastructure engineers and platform teams. You will learn how to design, build, optimize, and operate reliable GPU-powered systems that power real-world AI workloads at scale.Inside the book: Architect and deploy high-performance GPU clustersOptimize inference pipelines for speed, cost, and efficiencyDesign and manage distributed training and serving architecturesImplement production-grade monitoring, scaling, and reliability practicesNavigate the trade-offs between on-prem, cloud, and hybrid environmentsWritten for engineers, architects, and technical leaders, this book bridges the gap between theoretical machine learning and the complex realities of running AI in production. Whether you are building your first GPU cluster or scaling an existing platform to thousands of accelerators, you will find actionable strategies and battle-tested patterns you can apply immediately.Clear, up-to-date, and focused on real engineering challenges, not hype. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Nº de ref. del artículo: 9798197947581
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EUR 40,00
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Se envía dentro de Estados Unidos de America
Se envía dentro de Estados Unidos de America
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AI Infrastructure Engineering (Paperback)
Impresión bajo demandaLibrería: CitiRetail, Stevenage, Reino Unido
Calificación del vendedor: 5 de 5 estrellas
Paperback. Condición: new. Paperback. Reactive PublishingMaster the full stack of modern AI infrastructure, from raw hardware to large-scale production systems.This practical guide delivers the essential knowledge and techniques used by today's AI infrastructure engineers and platform teams. You will learn how to design, build, optimize, and operate reliable GPU-powered systems that power real-world AI workloads at scale.Inside the book: Architect and deploy high-performance GPU clustersOptimize inference pipelines for speed, cost, and efficiencyDesign and manage distributed training and serving architecturesImplement production-grade monitoring, scaling, and reliability practicesNavigate the trade-offs between on-prem, cloud, and hybrid environmentsWritten for engineers, architects, and technical leaders, this book bridges the gap between theoretical machine learning and the complex realities of running AI in production. Whether you are building your first GPU cluster or scaling an existing platform to thousands of accelerators, you will find actionable strategies and battle-tested patterns you can apply immediately.Clear, up-to-date, and focused on real engineering challenges, not hype. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Nº de ref. del artículo: 9798197947581
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AI Infrastructure Engineering : Building GPU Systems, Optimizing Inference, Designing Distributed Architectures, and Running Production Deployments
Librería: AHA-BUCH GmbH, Einbeck, Alemania
Calificación del vendedor: 5 de 5 estrellas
Taschenbuch. Condición: Neu. Neuware - Reactive PublishingMaster the full stack of modern AI infrastructure, from raw hardware to large-scale production systems.This practical guide delivers the essential knowledge and techniques used by today's AI infrastructure engineers and platform teams. You will learn how to design, build, optimize, and operate reliable GPU-powered systems that power real-world AI workloads at scale.Inside the book: - Architect and deploy high-performance GPU clusters- Optimize inference pipelines for speed, cost, and efficiency- Design and manage distributed training and serving architectures- Implement production-grade monitoring, scaling, and reliability practices- Navigate the trade-offs between on-prem, cloud, and hybrid environmentsWritten for engineers, architects, and technical leaders, this book bridges the gap between theoretical machine learning and the complex realities of running AI in production. Whether you are building your first GPU cluster or scaling an existing platform to thousands of accelerators, you will find actionable strategies and battle-tested patterns you can apply immediately.Clear, up-to-date, and focused on real engineering challenges, not hype. Nº de ref. del artículo: 9798197947581
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EUR 54,76
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AI Infrastructure Engineering
Librería: Rarewaves.com UK, London, Reino Unido
Calificación del vendedor: 5 de 5 estrellas
Paperback. Condición: New. Nº de ref. del artículo: LU-9798197947581
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EUR 37,53
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Se envía de Reino Unido a Estados Unidos de America
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