[Video tutorial] Train a Linear Classifier on Encrypted Data Using Concrete ML and Fully Homomorphic Encryption (FHE)

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 short video tutorial, Luis Montero, machine learning engineer at Zama walks you through one of the latest feature of Concrete ML: FHE training.

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Additional links

• Star the Concrete ML Github repository to endorse our work.
• Review the Concrete ML documentation.
• Get support on our community channels.
• Help us advance the FHE space with the Zama Bounty Program & Grant Program.

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