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Название: Practical Data Privacy: Enhancing Privacy and Security in Data (6th Early Release)
Автор: Katharine Jarmul
Издательство: O’Reilly Media, Inc.
Год: 2023-03-02
Страниц: 384
Язык: английский
Формат: epub
Размер: 10.6 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 emerging technologies and techniques in the field. Federated Learning (FL) and distributed Data Science provide new ways to think about how you do data analysis by keeping data at the edge: on phones, laptops, edge services — or even on-premise architecture or separate cloud architecture when working with partners. The data is not collected or copied to your own cloud or storage before you do analysis or Machine Learning.
Автор: Katharine Jarmul
Издательство: O’Reilly Media, Inc.
Год: 2023-03-02
Страниц: 384
Язык: английский
Формат: epub
Размер: 10.6 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 emerging technologies and techniques in the field. Federated Learning (FL) and distributed Data Science provide new ways to think about how you do data analysis by keeping data at the edge: on phones, laptops, edge services — or even on-premise architecture or separate cloud architecture when working with partners. The data is not collected or copied to your own cloud or storage before you do analysis or Machine Learning.