ramsyana/RustTensor
A learning-focused, high-performance tensor computation library built from scratch in Rust, featuring automatic differentiation and CPU/CUDA backends.
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.
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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.
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Language
Rust
License
MIT
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Last pushed
May 31, 2025
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