We'll learn how to apply core privacy principles and techniques to the data science and machine learning workflows. We'll also look at how to experiment with Python open-source libraries to ensure privacy-preservation in machine learning.
- Follow the instructions at this link
Katharine Jarmul is a privacy activist and data scientist whose work and research focus on privacy and security in data science workflows. She recently authored Practical Data Privacy for O'Reilly and works as a Principal Data Scientist at Thoughtworks. Katharine has held numerous leadership and independent contributor roles at large companies and startups in the US and Germany - implementing data processing and machine learning systems with privacy and security built-in and developing forward-looking, privacy-first data strategy.
This workshop was set up by @pyladiesams