This repository contains a collection of Rust functions aimed at facilitating machine learning tasks. These functions cover a range of algorithms for measuring similarity and distance between data points, essential for tasks such as clustering, classification, and data analysis.

The primary goal of this repository is educational. The functions are implemented to help understand how basic algorithms used in machine learning can be coded and optimized in Rust. This project is not focused on perfect optimization, but rather on learning and experimenting with Rust's capabilities in a machine learning context.

Feel free to contribute as you would like! If you have any suggestions or improvements, please submit a pull request.

I'm hoping to go back through Elements of Statistical Learning and write functions for each of the models in that book using rust and just math. That's a future project though and might be grafted on here or might be a different repo.