Artificial Intelligence Using Federated Learning

Artificial Intelligence Using Federated Learning

  • Ahmed A Elngar
  • Diego Oliva
  • Valentina E. Balas
Publisher:CRC PressISBN 13: 9781040266694ISBN 10: 104026669X

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Know about the book -

Artificial Intelligence Using Federated Learning is written by Ahmed A Elngar and published by CRC Press. It's available with International Standard Book Number or ISBN identification 104026669X (ISBN 10) and 9781040266694 (ISBN 13).

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.