Privacy-Preserving Machine Learning

Discover the essential insights into the world of privacy-preserving machine learning with Privacy-Preserving Machine Learning by Jin Li. Published by Springer Verlag in 2022, this paperback edition spans 88 pages and offers a comprehensive overview of the significant advancements in privacy-preserving techniques over the past decade. Delve into the critical importance of safeguarding privacy in machine learning applications and explore various schemes that have emerged to protect sensitive data. This book is an invaluable resource for researchers, practitioners, and anyone interested in the intersection of privacy and technology. Enhance your understanding of this rapidly evolving field with this authoritative guide.