Federated Learning with Python
Design and implement a federated learning system and develop applications using existing frameworks
Kiyoshi Nakayama, PhD
George Jeno
BIRMINGHAM—MUMBAI
Federated Learning with Python
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Acknowledgments
We would like to thank Dr. Norikazu Furukawa for contributing to Chapter 1, Challenges in Big Data and Traditional AI, and Anthony Maddalone for contributing to Chapter 9, Case Studies with Key Use Cases of Federated Learning Applications, with their great insight into current trends, challenges, and ongoing efforts in the machine learning field and also its future direction. We also thank Dr. Genya Ishigaki for his contribution to the code of the GitHub repository used throughout this book. We acknowledge the contribution of Dr. Jose Barreiros to the content related to the robotics use case.
Contributors
About the authors
Kiyoshi Nakayama, PhD, is the founder and CEO of TieSet Inc., which leads the development and dissemination of one of the most advanced distributed and federated learning platforms in the world. Before founding TieSet, he was a research scientist at NEC Laboratories America, renowned for having the world’s top-notch machine learning research group of researchers. He was also a postdoctoral researcher at Fujitsu Laboratories of America, where he implemented a distributed system for smart energy. He has published several international articles and patents and received the best paper award twice in his career. Kiyoshi received his PhD in computer science from the University of California, Irvine.
George Jeno is a co-founder of TieSet Inc. and has been a tech lead for the development of the STADLE federated learning platform. He has a deep understanding of machine learning theory and system architecture design, and he has leveraged this knowledge to research new algorithms and applications for distributed and federated learning. He holds a master’s degree in computer science (with a specialization in machine learning) from Georgia Tech.
About the reviewer
Sougata Pal is a passionate technology specialist, working as an enterprise architect in software architecture design and application scalability management, team building, and management. With over 15 years of experience, she has worked with different start-ups and large-scale enterprises to develop their business application infrastructures, enhancing their reach to customers. Having contributed to different open source projects on GitHub to empower the open source community, for the last couple of years, Sougata has been playing around with federated learning and cybersecurity algorithms to enhance the performance of cybersecurity processes by introducing concepts of federated learning.