English | 2023 | ISBN: 9781098129453 | 384 Pages | EPUB | 11 MB

Between major privacy regulations like the GDPR and CCPA and expensive and notorious data breaches, there has never been so much pressure for data scientists to ensure data privacy. Unfortunately, integrating privacy into your data science workflow is still complicated. This essential guide will give you solid advice and best practices on breakthrough privacy-enhancing technologies such as encrypted learning and differential privacy–as well as a look at emeg technologies and techniques in the field.