Artificial Intelligence Using Federated Learning

Language: English

Published by Taylor and Francis Ltd, GB, 2024

103277164X / 9781032771649

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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.

Seller Inventory # LU-9781032771649

Title
Artificial Intelligence Using Federated Learning
Author
Ahmed A Elngar
Publisher
Taylor and Francis Ltd, GB
Publication year
2024
Condition
New
Binding
Hardback
Language
English
ISBN 10
103277164X
ISBN 13
9781032771649
Item weight
580 grams

Rarewaves.com USA

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