Handbook on Federated Learning

Discover the transformative potential of federated learning with the Handbook on Federated Learning by Krishnan Saravanan. Published by Taylor & Francis Ltd in 2025, this comprehensive guide spans 356 pages and delves into the intricacies of this innovative Distributed Machine Learning model.

Federated learning is revolutionizing the way machine learning is applied across various industries. By leveraging the computational power of edge devices, this approach allows for the execution of models using local datasets, ensuring data privacy and efficiency. Whether you're a researcher, practitioner, or enthusiast, this handbook is an essential resource for understanding and implementing federated learning in real-world applications.

Enhance your knowledge and stay ahead in the fast-evolving field of machine learning with this insightful publication. Order your copy today and explore the future of decentralized machine learning!