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Federated Learning: From Theory to Practice

Federated Learning: From Theory to Practice

Hardcover

General ComputersProbability & StatisticsProgramming

Currently unavailable to order

ISBN10: 9819510082
ISBN13: 9789819510085
Publisher: Springer
Published: Jan 3 2026
Pages: 213
Weight: 1.00
Height: 0.77 Width: 6.44 Depth: 9.34
Language: English
How can we train powerful machine learning models together--across smartphones, hospitals, or financial institutions--without ever sharing raw data? This book delivers a compelling answer through the lens of federated learning (FL), a cutting-edge paradigm for decentralized, privacy-preserving machine learning. Designed for students, engineers, and researchers, this book offers a principled yet practical roadmap to building secure, scalable, and trustworthy FL systems from scratch.

Also from

Jung, Alexander

Also in

Probability & Statistics