Handbook on Federated Learning

Discover the cutting-edge world of federated learning with the Handbook on Federated Learning by Saravanan Krishnan. Published by Taylor & Francis Ltd in 2023, this comprehensive guide spans 356 pages and delves into the transformative potential of distributed machine learning. Federated learning enables edge devices to utilize their computational power effectively by executing models on local datasets, making it a pivotal technology in today's data-driven landscape. This handbook is an essential resource for researchers and practitioners alike, providing valuable insights and practical applications of federated learning across various domains. Enhance your understanding of this innovative approach and its implications for the future of machine learning.