Concrete ML v1.6 improves latency on large neural networks and supports pre-trained tree-based models with many other improvements
In this tutorial, Zama team member Roman Bredehoft, shows you how to work with encrypted DataFrames using Concrete ML.
Concrete ML v1.5 introduces a new DataFrame API and a new option that speeds up neural networks.
Zama Concrete ML now supports training of Logistic Regression models on encrypted data.
A tutorial on how to code a privacy-preserving version of Shazam using Zama Concrete ML.
This tutorial walks you through one of the latest features of Concrete ML: FHE training.