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Concrete ML is an open-source, privacy-preserving, machine learning framework based on Fully Homomorphic Encryption (FHE). |
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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. | start1.png | getting-started |
| Installation | Follow the step-by-step guide to install Concrete ML in your project. | start2.png | pip_installing.md |
| Key concepts | Understand important cryptographic concepts to implement Concrete ML. | start3.png | concepts.md |
Start building with Concrete ML by exploring its core features, discovering essential guides, and learning more with user-friendly tutorials.
| Fundamentals | Explore core features. | build1.png | ||
| Guides | Deploy your projects. | build2.png | ||
| Tutorials | Learn more with tutorials. | build3.png |
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.
Collaborate with us to advance the FHE spaces and drive innovation together.
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