Machine Learning over Encrypted Data with Fully Homomorphic Encryption

Presenters:
Benoit Chevallier-Mames, Lead of Machine Learning, Zama
Jordan Frery, Research Scientist, Zama
Machine learning over encrypted data is possible thanks to Fully Homomorphic Encryption. The gap for data scientists appears huge. They seem to need to acquire new cryptographic knowledge and cannot leverage their popular frameworks. This session will show this is not true by presenting a new open source library that allows practitioners to implement machine learning models using only already known tools.
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