This repository contains the source of "The Rust Machine Learning Book".

The aim of this book is to demonstrate how the Rust language can be used for Machine Learning tasks. They encompass classical ML algorithms, like linear regression and KMeans clustering, but also more modern approaches. Most of the classical algorithms are contained in the rust-ml/linfa crate and ready to use.

The reader should have a basic knowledge of Rust type-system and linear algebra. A small recap on rust-ndarray type system should familiarize the reader with its applications and limitations.

Building this book requires mdBook.

$ cargo install mdbook

You can build the book with

$ mdbook build

and append

$ mdbook build --open
# 
$ mdbook serve

in order to open it afterwards.

Code samples are contained in the examples/ directory, and can be built as a group or individually using:

$ cargo build --all
# or
$ cargo run --example name_of_algorithm

By default, all plots will be written to the target/ directory, so as not to be indexed by git.