[Video tutorial] Work With Encrypted DataFrames Using Concrete ML

Concrete ML is a Privacy-Preserving Machine Learning set of tools that aims to simplify the use of Fully Homomorphic Encryption (FHE) for developers so they can automatically turn machine learning models into their homomorphic equivalent.

In this tutorial, Zama team member Roman Bredehoft, shows you how to work with encrypted DataFrames using Concrete ML.

Additional links

• Star the Concrete ML Github repository to endorse our work.
• Review the Concrete ML documentation.
• Get support on our Community Forum.
• Help us advance the FHE space with the Zama Bounty Program.
• Participate in our 5-Question Developer Survey