Da: PBShop.store UK, Fairford, GLOS, Regno Unito
EUR 134,29
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Aggiungi al carrelloHRD. Condizione: New. New Book. Shipped from UK. Established seller since 2000.
Da: GreatBookPrices, Columbia, MD, U.S.A.
EUR 132,46
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Da: GreatBookPricesUK, Woodford Green, Regno Unito
EUR 134,27
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Da: Ria Christie Collections, Uxbridge, Regno Unito
EUR 142,80
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Da: GreatBookPrices, Columbia, MD, U.S.A.
EUR 142,06
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Da: GreatBookPricesUK, Woodford Green, Regno Unito
EUR 146,17
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Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 161,68
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Aggiungi al carrelloBuch. Condizione: Neu. Neuware - Comprehensive overview of the fledgling domain of federated learning (FL), explaining emerging FL methods, architectural approaches, enabling frameworks, and applications.
Da: CitiRetail, Stevenage, Regno Unito
EUR 150,28
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Aggiungi al carrelloHardcover. Condizione: 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. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
Da: Books Puddle, New York, NY, U.S.A.
EUR 181,87
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Da: Grand Eagle Retail, Fairfield, OH, U.S.A.
EUR 152,83
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Aggiungi al carrelloHardcover. Condizione: 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. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Da: AussieBookSeller, Truganina, VIC, Australia
EUR 190,14
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Aggiungi al carrelloHardcover. Condizione: 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. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
Da: Kennys Bookshop and Art Galleries Ltd., Galway, GY, Irlanda
Prima edizione
EUR 220,61
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Aggiungi al carrelloCondizione: New. 2024. 1st Edition. hardcover. . . . . .
Da: Kennys Bookstore, Olney, MD, U.S.A.
EUR 270,69
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Aggiungi al carrelloCondizione: New. 2024. 1st Edition. hardcover. . . . . . Books ship from the US and Ireland.
Da: Revaluation Books, Exeter, Regno Unito
EUR 190,99
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Aggiungi al carrelloHardcover. Condizione: Brand New. 432 pages. 7.00x0.94x10.00 inches. In Stock. This item is printed on demand.