Abstract
A brief tutorial and demo on using TF Privacy, Tensorflow's open-source library for differentially private stochastic gradient descent (DP-SGD). We will show how to easily write code that implements DP-SGD, talk about practical considerations in training, and show how to analyze the privacy parameters of the resulting model.