deeplearn-rs
A proof-of-concept neural network library in Rust with implementations for MNIST digit recognition and char-rnn LSTM models.
What is deeplearn-rs?
deeplearn-rs is a proof-of-concept deep learning library implemented in Rust that provides basic neural network components for building and training models. It currently supports MNIST handwritten digit recognition and character-level LSTM models, serving as an educational tool for understanding neural network implementation in systems programming languages.
Rust developers interested in learning about neural network implementation and machine learning researchers looking for a basic, readable deep learning framework in a systems language.
Developers choose deeplearn-rs for its readable codebase, portability, and the ability to have more control over neural network components while experimenting with deep learning concepts in Rust.
Overview
Neural networks in Rust
Use Cases
Best For
- Learning neural network implementation in Rust
- Experimenting with basic MNIST digit recognition models
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