English | 2022 | ISBN: 978-1617298042 | 323 pages | True PDF | 13.24 MB
Complex privacy-enhancing technologies are demystified through real-world use cases for facial recognition, cloud data storage, and more.
Privacy-Preserving Machine Learning is a practical guide to keeping ML data anonymous and secure. You'll learn the core principles behind different privacy preservation technologies, and how to put theory into practice for your own machine learning.
