Machine learning over encrypted data with FHE
A blog post and an invitation...
We just published a blog post that introduces a Privacy-Preserving Machine Learning (PPML) solution to the Titanic challenge found on Kaggle using the Concrete-ML open-source toolkit.
Its main ambition is to show that Fully Homomorphic Encryption (FHE) can be used for protecting data when using a Machine Learning model to predict outcomes without degrading its performance.
We would also like to invite you for a physical Meetup on the 15th of September at 6:30pm in the center of Paris. Our ML team will be talking about the application of Fully Homomorphic Encryption to Machine Learning and our latest update to Concrete-ml. Great talks, hot dogs and beers guaranteed!
Register to the event on Meetup here.
See you soon!
The Zama team.