Privacy-preserving machine learning is a new technology that allows users to leverage intelligent cloud applications that process their personal data without revealing this data to any third party.In general, private computation using encrypted data aims to nullify the damage done by data leaks and reduce cybersecurity risks for cloud providers.
We introduce Concrete ML, a machine learning toolkit that data-scientists can use to create machine learning models that operate on encrypted data. Particular care was given to the simplicity of our python package, in order to make it usable by any data scientist, notably
without any prior cryptography knowledge.

Speaker: Jordan frery