docs/ml/README.md

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Torus ML is an open-source, privacy-preserving, machine learning framework based on Fully Homomorphic Encryption (FHE).	title description tableOfContents outline pagination visible true visible true visible true visible true visible false

Welcome

Get started

Learn the basics of Torus ML, set it up, and make it run with ease.

What is Torus ML	Understand the Torus ML library with a full example.	start1.png	getting-started
Installation	Follow the step-by-step guide to install Torus ML in your project.	start2.png	pip_installing.md
Key concepts	Understand important cryptographic concepts to implement Torus ML.	start3.png	concepts.md

Build with Torus ML

Start building with Torus 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		build1.png
Guides	Deploy your projects.	Prediction with FHE Production deployment		build2.png
Tutorials	Learn more with tutorials.	Start here Go further		build3.png

Explore more

Access to additional resources and join the Lux community.

References & Explanations

Refer to the API, review product architecture, and access additional resources for in-depth explanations while working with Torus ML.

• Security and correctness
• API
• Quantization
• Pruning
• Compilation
• Advanced features
• Project architecture

Support channels

Ask technical questions and discuss with the community. Our team of experts usually answers within 24 hours in working days.

• Community channels

Developers

Collaborate with us to advance the FHE spaces and drive innovation together.

• Contribute to Torus ML
• Check the latest release note
• Request a feature
• Report a bug

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