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Ajouter au panierEtat : New. 1st edition NO-PA16APR2015-KAP.
Vendeur : Brook Bookstore On Demand, Napoli, NA, Italie
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Ajouter au panierHRD. Etat : New. New Book. Shipped from UK. Established seller since 2000.
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Ajouter au panierEtat : As New. Unread book in perfect condition.
Vendeur : GreatBookPricesUK, Woodford Green, Royaume-Uni
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Vendeur : Ria Christie Collections, Uxbridge, Royaume-Uni
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Ajouter au panierEtat : New. In.
Vendeur : GreatBookPricesUK, Woodford Green, Royaume-Uni
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Ajouter au panierEtat : As New. Unread book in perfect condition.
Vendeur : THE SAINT BOOKSTORE, Southport, Royaume-Uni
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Ajouter au panierHardback. Etat : New. New copy - Usually dispatched within 4 working days.
Vendeur : Kennys Bookshop and Art Galleries Ltd., Galway, GY, Irlande
Edition originale
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Ajouter au panierEtat : New. 2024. 1st Edition. hardcover. . . . . .
Vendeur : moluna, Greven, Allemagne
EUR 141,79
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Ajouter au panierEtat : New.
Langue: anglais
Edité par JOHN WILEY NP (ORIGINAL)45, 2024
ISBN 10 : 1394219210 ISBN 13 : 9781394219216
Vendeur : UK BOOKS STORE, London, LONDO, Royaume-Uni
EUR 208
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Ajouter au panierEtat : New. Brand New ! Fast Delivery "International Edition " and ship within 24-48 hours. Deliver by FedEx and Dhl, & Aramex, UPS, & USPS and we do accept APO and PO BOX Addresses. Order can be delivered worldwide within 4-6 Working days .and we do have flat rate for up to 2LB. Extra shipping charges will be requested This Item May be shipped from India, United states & United Kingdom. Depending on your location and availability.
Vendeur : Kennys Bookstore, Olney, MD, Etats-Unis
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Ajouter au panierEtat : New. 2024. 1st Edition. hardcover. . . . . . Books ship from the US and Ireland.
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
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Ajouter au panierBuch. Etat : Neu. Neuware - Comprehensive overview of the fledgling domain of federated learning (FL), explaining emerging FL methods, architectural approaches, enabling frameworks, and applications.
Vendeur : Grand Eagle Retail, Bensenville, IL, Etats-Unis
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Ajouter au panierHardcover. Etat : new. Hardcover. Comprehensive overview of the fledgling domain of federated learning (FL), explaining emerging FL methods, architectural approaches, enabling frameworks, and applications Model Optimization Methods for Efficient and Edge AI explores AI model engineering, evaluation, refinement, optimization, and deployment across multiple cloud environments (public, private, edge, and hybrid). It presents key applications of the AI paradigm, including computer vision (CV) and Natural Language Processing (NLP), explaining the nitty-gritty of federated learning (FL) and how the FL method is helping to fulfill AI model optimization needs. The book also describes tools that vendors have created, including FL frameworks and platforms such as PySyft, Tensor Flow Federated (TFF), FATE (Federated AI Technology Enabler), Tensor/IO, and more. The first part of the text covers popular AI and ML methods, platforms, and applications, describing leading AI frameworks and libraries in order to clearly articulate how these tools can help with visualizing and implementing highly flexible AI models quickly. The second part focuses on federated learning, discussing its basic concepts, applications, platforms, and its potential in edge systems (such as IoT). Other topics covered include: Building AI models that are destined to solve several problems, with a focus on widely articulated classification, regression, association, clustering, and other prediction problemsGenerating actionable insights through a variety of AI algorithms, platforms, parallel processing, and other enablersCompressing AI models so that computational, memory, storage, and network requirements can be substantially reducedAddressing crucial issues such as data confidentiality, data access rights, data protection, and access to heterogeneous dataOvercoming cyberattacks on mission-critical software systems by leveraging federated learning Written in an accessible manner and containing a helpful mix of both theoretical concepts and practical applications, Model Optimization Methods for Efficient and Edge AI is an essential reference on the subject for graduate and postgraduate students, researchers, IT professionals, and business leaders. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Vendeur : CitiRetail, Stevenage, Royaume-Uni
EUR 147,67
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Ajouter au panierHardcover. Etat : new. Hardcover. Comprehensive overview of the fledgling domain of federated learning (FL), explaining emerging FL methods, architectural approaches, enabling frameworks, and applications Model Optimization Methods for Efficient and Edge AI explores AI model engineering, evaluation, refinement, optimization, and deployment across multiple cloud environments (public, private, edge, and hybrid). It presents key applications of the AI paradigm, including computer vision (CV) and Natural Language Processing (NLP), explaining the nitty-gritty of federated learning (FL) and how the FL method is helping to fulfill AI model optimization needs. The book also describes tools that vendors have created, including FL frameworks and platforms such as PySyft, Tensor Flow Federated (TFF), FATE (Federated AI Technology Enabler), Tensor/IO, and more. The first part of the text covers popular AI and ML methods, platforms, and applications, describing leading AI frameworks and libraries in order to clearly articulate how these tools can help with visualizing and implementing highly flexible AI models quickly. The second part focuses on federated learning, discussing its basic concepts, applications, platforms, and its potential in edge systems (such as IoT). Other topics covered include: Building AI models that are destined to solve several problems, with a focus on widely articulated classification, regression, association, clustering, and other prediction problemsGenerating actionable insights through a variety of AI algorithms, platforms, parallel processing, and other enablersCompressing AI models so that computational, memory, storage, and network requirements can be substantially reducedAddressing crucial issues such as data confidentiality, data access rights, data protection, and access to heterogeneous dataOvercoming cyberattacks on mission-critical software systems by leveraging federated learning Written in an accessible manner and containing a helpful mix of both theoretical concepts and practical applications, Model Optimization Methods for Efficient and Edge AI is an essential reference on the subject for graduate and postgraduate students, researchers, IT professionals, and business leaders. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
Vendeur : Revaluation Books, Exeter, Royaume-Uni
EUR 180,11
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Ajouter au panierHardcover. Etat : Brand New. 432 pages. 7.00x0.94x10.00 inches. In Stock. This item is printed on demand.