Overview of Machine Learning Libraries in Rust

Rust does not have a single built-in machine learning library; instead, you use community crates like linfa for general ML or burn for deep learning. Add the crate to your Cargo.toml and import it in your code to start building models.

[dependencies]
linfa = "0.7"

use linfa::traits::SupervisedLearner;

fn main() {
    // Initialize a model and train it
    let model = linfa::linear_regression::LinearRegression::default();
    // model.fit(&dataset).unwrap();
}

Rust relies on external packages called crates to handle machine learning tasks rather than having them built-in. You pick a specific crate like linfa for standard algorithms or burn for neural networks and add it to your project. It is like choosing a specific tool from a toolbox rather than having one giant tool that does everything.