This repository is a curated list of machine learning libraries and resources written in Rust, targeting developers considering a migration from Python. It aims to provide a comprehensive overview of the Rust ML ecosystem, including libraries for data manipulation, visualization, deep learning, and various ML algorithms, with commentary on their utility and maintenance status.
How It Works
The repository functions as a categorized directory, meticulously listing and briefly describing Rust libraries for machine learning tasks. It organizes these resources into logical sections such as "Dataframe," "Image Processing," "Natural Language Processing," and "Deep Neural Network," among others. Each entry includes links to the respective GitHub repositories, relevant blog posts, tutorials, and research papers, offering a structured approach to exploring Rust's ML capabilities.
Quick Start & Requirements
- Installation and usage vary by individual library.
- Prerequisites often include Rust toolchain, and specific libraries may require CUDA, Python bindings, or other external dependencies.
- Setup time and resource requirements are library-dependent.
- Relevant links to official documentation, tutorials, and examples are provided for each listed resource.
Highlighted Details
- Comprehensive coverage of libraries for data manipulation (e.g., Polars, ndarray), visualization (e.g., plotters, plotly), and core ML algorithms.
- Detailed sections on Natural Language Processing (NLP) with libraries for tokenization, language detection, and transformer models.
- Extensive listings for Deep Neural Networks, including bindings for TensorFlow and PyTorch, and pure Rust tensor libraries.
- Resources for GPU computing in Rust, covering libraries like Rust-GPU and bindings for TensorRT.
Maintenance & Community
- The project is community-driven, with contributions encouraged via README updates.
- Links to related "awesome" lists and community discussions on platforms like Reddit and the Rust Programming Language Forum are provided.
Licensing & Compatibility
- Licenses vary by individual library; users must consult each library's specific license.
- Compatibility for commercial use or closed-source linking depends on the licenses of the individual Rust ML libraries.
Limitations & Caveats
- The list includes libraries that are no longer maintained, requiring users to assess project health.
- Some entries may be experimental or have limited documentation, necessitating careful evaluation.