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Springer Federated Learning: Fundamentals and Advances - Machine Learning

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£103.31 £91.97 £94.44 £96.92 £99.39 £101.87 £104.34 01 August 2026 16 August 2026 01 September 2026 17 September 2026 03 October 2026
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Description

Federated Learning: Fundamentals and Advances is a comprehensive guide from Springer that explores the principles, methodologies and cutting-edge developments in federated learning systems. This book covers the foundational concepts essential for understanding distributed machine learning across decentralised networks, making it invaluable for researchers, practitioners and students working in AI and machine learning. Part of Springer's Machine Learning: Foundations, Methodologies, and Applications series, this text bridges theory and practice, providing readers with both conceptual frameworks and real-world applications of federated learning technologies. Whether you are developing privacy-preserving machine learning solutions or studying advanced distributed systems, this resource offers depth and clarity on one of the most important paradigms shaping modern artificial intelligence.

Key Features

Springer publishing authority ensures rigorous peer-reviewed content on federated learning theory and practice.

Covers foundational principles and advanced topics in federated learning systems for researchers and practitioners.

Part of the Machine Learning: Foundations, Methodologies, and Applications series, aligning with comprehensive AI curricula.

Explores distributed machine learning approaches essential for privacy-preserving and decentralised AI applications.

Provides both methodological frameworks and real-world case studies relevant to contemporary machine learning challenges.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
30 November 2022
Listed Since
30 August 2022

Barcode

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