Privacy-Preserving Machine Learning

Techniques and methods for training and deploying machine learning models while protecting the privacy of training data, user data and model parameters.

An umbrella term for all the techniques that let you build and use AI while keeping personal data private. It's the toolbox for building smart systems without being creepy about people's data.

Privacy-preserving techniques are increasingly expected by regulators and customers. Your AI strategy should incorporate these approaches to enable AI innovation while meeting privacy obligations and building trust with data subjects.