ramsyana/RustTensor

A learning-focused, high-performance tensor computation library built from scratch in Rust, featuring automatic differentiation and CPU/CUDA backends.

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Experimental

This is a learning-focused project for building machine learning models from the ground up. It takes numerical data like images or text sequences, processes them through custom-built neural network components, and produces trained models capable of making predictions or classifications. It's designed for machine learning engineers, researchers, or students who want to deeply understand how neural networks and their underlying computations truly work.

No commits in the last 6 months.

Use this if you are a machine learning engineer or researcher interested in exploring the foundational mechanics of deep learning frameworks and building custom models with granular control in Rust, especially for educational or experimental purposes.

Not ideal if you need a production-ready, highly optimized, and feature-complete deep learning framework with a stable API and extensive pre-built models, as this library is primarily for educational exploration and active development.

deep-learning neural-networks machine-learning-engineering gpu-acceleration algorithm-development
Stale 6m No Package No Dependents
Maintenance 2 / 25
Adoption 9 / 25
Maturity 15 / 25
Community 3 / 25

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Stars

70

Forks

1

Language

Rust

License

MIT

Last pushed

May 31, 2025

Commits (30d)

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