The field of privacy in machine learning is becoming increasingly important. With legislation like GDPR, it is becoming necessary for us, data scientists, to be mindful about privacy concerns related to the applications we develop. In this episode we interview Ran Gilad Bachrach, a researcher at Microsoft Research, that tells us about privacy in machine learning. We'll talk about differential privacy, about homomorphic encryption and how it enables training models on encrypted data, and about secure multi party computation - a field who's goal is to help different parties train models together, even when they can't share their data with one-another.

This episode is sponsored by sisense. They're hiring data scientists! find our more on https://www.sisense.com/careers/