A quick guide to differential privacy

One method for privacy-preserving machine learning

TL;DR

This newsletter is about differential privacy. It looks at what it is, how it works and some practical applications of this solution, including for the development of machine learning models.

Here are the key takeaways:

• Differential privacy is about quantifying the information leakage of an algorithm. This leakage is measured by using the algorithm i…