Book
Author: Katharine Jarmul
Put privacy at the forefront of your data science, analytics and machine learning projects
Integrating privacy into data systems might be difficult, but today it’s urgent. In an environment of rapidly changing regulations and increased public awareness, it’s essential that data professionals see themselves as the front line in ensuring privacy is protected — for both consumers and their organizations.
In Practical Data Privacy, Katharine Jarmul explains how data professionals can be proactive in responding to privacy demands and take the lead in putting privacy principles at the forefront of data science, machine learning, data engineering and data management.
Covering everything from data governance and anonymization to federated and encrypted learning, Practical Data Privacy bridges the gap between data science, engineering and security, and guides you through what’s happening at the cutting edge.
Embed privacy principles in data science pipelines
Master a rapidly changing regulatory environment
Explore federated and encrypted learning
Read the first chapter for free
Take a look inside Katharine Jarmul's new book using the PDF reader on the left or click the button below to download a copy.
Katharine Jarmul
Principal Data ScientistKatharine Jarmul is a Principal Data Scientist at Thoughtworks Germany. Previously, she has held numerous roles at large companies and startups in the US and Germany, implementing data processing and machine learning systems with a focus on reliability, testability, privacy and security.
She is a passionate and internationally recognized data scientist, programmer and lecturer. Katharine is also a frequent keynote speaker at international software and AI conferences.
Some data scientists see privacy as something that gets in their way. If you're not one of them, if you believe privacy is morally and commercially desirable, if you appreciate the rigor and wonder in engineering privacy, if you want to understand the state of the art of the field, then Katharine Jarmul's book is for you.
Some data scientists see privacy as something that gets in their way. If you're not one of them, if you believe privacy is morally and commercially desirable, if you appreciate the rigor and wonder in engineering privacy, if you want to understand the state of the art of the field, then Katharine Jarmul's book is for you.
