Artificial Intelligence Using Federated (25 results)
- Softcover
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- Softcover
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- Softcover
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- Softcover
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- Softcover
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Artificial Intelligence Using Federated Learning: Fundamentals, Challenges, And Applications
Balas, Valentina E. (Editor)/ Oliva, Diego (Editor)/ Elngar, Ahmed A (Editor)
- Softcover
Seller: Revaluation Books, Exeter, United KingdomRevaluation Books
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£ 84.86
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Paperback. Condition: Brand New. 294 pages. 6.14x0.65x9.21 inches. In Stock.
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- Softcover
Seller: moluna, Greven, Germanymoluna
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£ 69.07
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Condition: New. Dr. Ahmed A. Elngar is an Associate Professor and Head of the Computer Science Department at the Faculty of Computers and Artificial Intelligence, Beni-Suef University, Egypt. He is the Founder and Head of the Scientific Innovation Research Group .
- Softcover
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
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Taschenbuch. Condition: Neu. Neuware - Federated machine learning is a novel approach to combining distributed machine learning, cryptography, security, and incentive mechanism design. It allows organizations to keep sensitive and private data on users or customers decentralized and secure, helping them comply with stringent dat…a protection regulations like GDPR and CCPA.Artificial Intelligence Using Federated Learning: Fundamentals, Challenges, and Applications enables training AI models on a large number of decentralized devices or servers, making it a scalable and efficient solution. It also allows organizations to create more versatile AI models by training them on data from diverse sources or domains. This approach can unlock innovative use cases in fields like healthcare, finance, and IoT, where data privacy is paramount.The book is designed for researchers working in Intelligent Federated Learning and its related applications, as well as technology development, and is also of interest to academicians, data scientists, industrial professionals, researchers, and students.
Artificial Intelligence Using Federated Learning : Fundamentals, Challenges and Applications
Elngar, Ahmed A. (EDT); Oliva, Diego (EDT); Balas, Valentina E. (EDT)
- Hardcover
Seller: GreatBookPrices, Columbia, MD, U.S.A.GreatBookPrices
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Artificial Intelligence Using Federated Learning : Fundamentals, Challenges and Applications
Elngar, Ahmed A. (EDT); Oliva, Diego (EDT); Balas, Valentina E. (EDT)
- Hardcover
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- Hardcover
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Artificial Intelligence Using Federated Learning : Fundamentals, Challenges and Applications
Elngar, Ahmed A. (EDT); Oliva, Diego (EDT); Balas, Valentina E. (EDT)
- Hardcover
Seller: GreatBookPricesUK, Woodford Green, United KingdomGreatBookPricesUK
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- Hardcover
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- Hardcover
Seller: PBShop.store US, Wood Dale, IL, U.S.A.PBShop.store US
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- Hardcover
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- Hardcover
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- Hardcover
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Artificial Intelligence Using Federated Learning : Fundamentals, Challenges and Applications
Elngar, Ahmed A. (EDT); Oliva, Diego (EDT); Balas, Valentina E. (EDT)
- Hardcover
Seller: GreatBookPricesUK, Woodford Green, United KingdomGreatBookPricesUK
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- Hardcover
Seller: Biblios, frankfurt am main, HESSE, GermanyBiblios
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- Hardcover
Seller: THE SAINT BOOKSTORE, Southport, United KingdomTHE SAINT BOOKSTORE
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Hardback. Condition: New. New copy - Usually dispatched within 4 working days.
Artificial Intelligence Using Federated Learning: Fundamentals, Challenges and Applications
Elngar, Ahmed A. (Editor)/ Oliva, Diego (Editor)/ Balas, Valentina E. (Editor)
- Hardcover
Seller: Revaluation Books, Exeter, United KingdomRevaluation Books
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£ 210.37
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Hardcover. Condition: Brand New. 344 pages. 9.18x6.12x9.21 inches. In Stock.
- Softcover
- Print on Demand
Seller: Grand Eagle Retail, Bensenville, IL, U.S.A.Grand Eagle Retail
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Paperback. Condition: new. Paperback. Federated machine learning is a novel approach to combining distributed machine learning, cryptography, security, and incentive mechanism design. It allows organizations to keep sensitive and private data on users or customers decentralized and secure, helping them comply with stringent data… protection regulations like GDPR and CCPA.Artificial Intelligence Using Federated Learning: Fundamentals, Challenges, and Applications enables training AI models on a large number of decentralized devices or servers, making it a scalable and efficient solution. It also allows organizations to create more versatile AI models by training them on data from diverse sources or domains. This approach can unlock innovative use cases in fields like healthcare, finance, and IoT, where data privacy is paramount.The book is designed for researchers working in Intelligent Federated Learning and its related applications, as well as technology development, and is also of interest to academicians, data scientists, industrial professionals, researchers, and students. Federated machine learning is a novel approach to combining distributed machine learning, cryptography, security, and incentive mechanism design. It allows organizations to keep sensitive and private data on users or customers decentralized and secure, helping them comply with stringent data protection regulations like GDPR and CCPA. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
- Softcover
- Print on Demand
Seller: CitiRetail, Stevenage, United KingdomCitiRetail
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£ 54.99
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Paperback. Condition: new. Paperback. Federated machine learning is a novel approach to combining distributed machine learning, cryptography, security, and incentive mechanism design. It allows organizations to keep sensitive and private data on users or customers decentralized and secure, helping them comply with stringent data… protection regulations like GDPR and CCPA.Artificial Intelligence Using Federated Learning: Fundamentals, Challenges, and Applications enables training AI models on a large number of decentralized devices or servers, making it a scalable and efficient solution. It also allows organizations to create more versatile AI models by training them on data from diverse sources or domains. This approach can unlock innovative use cases in fields like healthcare, finance, and IoT, where data privacy is paramount.The book is designed for researchers working in Intelligent Federated Learning and its related applications, as well as technology development, and is also of interest to academicians, data scientists, industrial professionals, researchers, and students. Federated machine learning is a novel approach to combining distributed machine learning, cryptography, security, and incentive mechanism design. It allows organizations to keep sensitive and private data on users or customers decentralized and secure, helping them comply with stringent data protection regulations like GDPR and CCPA. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
- Hardcover
- Print on Demand
Seller: Basi6 International, Irving, TX, U.S.A.Basi6 International
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Condition: Brand New. New. US edition. Print on demand title. Delivery takes 20-25 days. Excellent Customer Service.
- Softcover
- Print on Demand
Seller: AussieBookSeller, Truganina, VIC, AustraliaAussieBookSeller
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£ 98.19
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Paperback. Condition: new. Paperback. Federated machine learning is a novel approach to combining distributed machine learning, cryptography, security, and incentive mechanism design. It allows organizations to keep sensitive and private data on users or customers decentralized and secure, helping them comply with stringent data… protection regulations like GDPR and CCPA.Artificial Intelligence Using Federated Learning: Fundamentals, Challenges, and Applications enables training AI models on a large number of decentralized devices or servers, making it a scalable and efficient solution. It also allows organizations to create more versatile AI models by training them on data from diverse sources or domains. This approach can unlock innovative use cases in fields like healthcare, finance, and IoT, where data privacy is paramount.The book is designed for researchers working in Intelligent Federated Learning and its related applications, as well as technology development, and is also of interest to academicians, data scientists, industrial professionals, researchers, and students. Federated machine learning is a novel approach to combining distributed machine learning, cryptography, security, and incentive mechanism design. It allows organizations to keep sensitive and private data on users or customers decentralized and secure, helping them comply with stringent data protection regulations like GDPR and CCPA. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
