Concrete ML is an open-source, privacy-preserving, machine learning framework based on Fully Homomorphic Encryption (FHE).
Learn the basics of Concrete ML, set it up, and make it run with ease.
What is Concrete ML
Understand the Concrete ML library with a full example.
Installation
Follow the step-by-step guide to install Concrete ML in your project.
Key concepts
Understand important cryptographic concepts to implement Concrete ML.
Start building with Concrete ML by exploring its core features, discovering essential guides, and learning more with user-friendly tutorials.
Fundamentals
Explore core features.
Built-in models
Deep learning
Guides
Deploy your projects.
Prediction with FHE
Production deployment
Tutorials
Learn more with tutorials.
Start here
Go further
Access to additional resources and join the Zama community.
Refer to the API, review product architecture, and access additional resources for in-depth explanations while working with Concrete ML.
Security and correctness
API
Quantization
Pruning
Compilation
Advanced features
Project architecture
Ask technical questions and discuss with the community. Our team of experts usually answers within 24 hours in working days.
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Collaborate with us to advance the FHE spaces and drive innovation together.
Contribute to Concrete ML
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Zama 5-Question Developer Survey
We want to hear from you! Take 1 minute to share your thoughts and helping us enhance our documentation and libraries. 👉 Click herearrow-up-right to participate.
Last updated 10 months ago
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