Applications of Federated Learning by S. Jayachitra (.ePUB)+
File Size: 19.4 MB
Applications of Federated Learning in Technological Advancements: Use Cases and Applications by S. Jayachitra, A. Prasanth, Rajesh Kumar Dhanaraj, Balasubramaniam S, Danilo Pelusi
Requirements: .ePUB, .PDF reader, 19.4 MB
Overview: This book explores the applications and advancements of federated learning across diverse sectors, focusing on its integration with cutting- edge technologies like Internet of Things (IoT), Artificial Intelligence (AI), blockchain, and digital twins. Real-world examples and case studies illustrate Federated Learning’s role in healthcare, smart cities, and maritime applications while addressing critical concerns such as security. It provides insights into Federated Learning’s transformative potential, offering practical strategies for intelligent systems and sustainable environments. FL method is a knowledge strategy that is part of Machine Learning. FL enables decentralized model training by allowing multiple devices or organizations to collaboratively develop a shared model without transferring their local data to a central server. It ensures that sensitive information remains on local devices, addressing privacy concerns while harnessing the power of distributed datasets. Several businesses have adopted FL integration in IoT by providing innovative, secure, and intelligent solutions across multiple domains. It involves intelligent and self-adapting vehicles that strengthen performance, safety, and production and can adjust to altering conditions naturally.
Genre: Non-Fiction > Tech & Devices
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