Google's open-sourced Differential Privacy library enables developers and organizations to learn from the majority of their data while simultaneously ensuring that those results do not allow any individual's data to be distinguished or re-identified. In this workshop, hosted by Google Safety Engineering Center, you will learn how to produce statistics that are preserving the user’s privacy by using differentially private aggregations. This workshop is geared towards startup developers, data scientists, business analysts, and product managers who work with or analyze personable identifiable datasets, who hope to improve their product offerings or plan to publish statistics based on datasets that require a robust data anonymization technique to protect their user’s privacy and prevent data leakages.
Participants need to be able to read and write Python to follow the workshop and understand the computational models.
When? February, 9 | 17:00 - 18:00
Where? Remote