This repository is a list of machine learning libraries written in Rust. It's a compilation of GitHub repositories, blogs, books, movies, discussions, papers, e
This repository is a list of machine learning libraries written in Rust. It's a compilation of GitHub repositories, blogs, books, movies, discussions, papers, e
This repository is a list of machine learning libraries written in Rust. It's a compilation of GitHub repositories, blogs, books, movies, discussions, papers. This repository is targeted at people who are thinking of migrating from Python.
It is divided into several basic library and algorithm categories. And it also contains libraries that are no longer maintained and small libraries. It has commented on the helpful parts of the code. It also commented on good libraries within each category.
We can find a better way to use Rust for Machine Learning.
evcxr can be handled as Jupyter Kernel or REPL. It is helpful for learning and validation.
It might want to try plotters for now.
ASCII line graph:
Examples:
Most things use ndarray or std::vec.
Also, look at nalgebra. When the size of the matrix is known, it is valid.
See also: ndarray vs nalgebra - reddit
It might want to try polars for now. datafusion looks good too.
It might want to try image-rs for now. Algorithms such as linear transformations are implemented in other libraries as well.
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