Understanding privacy involves knowing the fundamentals of differential privacy and federated learning systems. There seems to be quite a lot of interest in the theory of privacy as well as knowing how to exactly deploy these systems.
This first primer in a long series of posts will provide the basics to get started with the theoretical foundations, basic implementations (open-source) and how to deploy it in research and industry.
The full series is hosted on GitHub at APrimerOnDifferentialPrivacy, along with a compiled list of relevant resources.
This post is part of a series. See the GitHub repo for all installments.