£140.58

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Springer Blockchain and Federated Learning Synergy for Privacy-Focused DeepFex Solutions

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Description

Explore the intersection of blockchain technology and federated learning in this comprehensive academic work from Springer. This book examines how distributed ledger systems can enhance privacy-preserving machine learning approaches, offering deep insights into DeepFex solutions and their practical applications. Designed for researchers, computer scientists, and professionals working in AI and machine learning, this publication provides essential knowledge on integrating blockchain technologies with federated learning frameworks to build secure, decentralised systems. Discover cutting-edge methodologies for protecting data privacy whilst maintaining computational efficiency in modern deep learning environments.

Key Features

Springer publishes this academic text on blockchain technologies and federated learning integration for advanced AI applications.

The book addresses privacy-focused DeepFex solutions, providing technical guidance for implementing secure distributed systems.

Comprehensive coverage of blockchain and federated learning synergy helps professionals understand decentralised machine learning architectures.

Ideal reference material for computer science researchers and AI practitioners seeking privacy-preserving deep learning methodologies.

Explores practical applications of blockchain technologies in federated learning environments for enhanced data protection.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
09 November 2025
Listed Since
15 July 2025

Barcode

No barcode data available

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