Introduction
Published in · 2 min read · Jan 14, 2024
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Welcome to the exciting world of AI with Rust! Rust, known for its performance and safety, is making significant inroads into AI and machine learning projects. In this post, we’ll explore how Rust can be used to build a machine learning model, specifically focusing on a linear regression example using the rusty-machine
library.
Setting Up the Rust Environment
To dive into Rust-based AI, you first need to set up your environment:
- Install Rust: Use the official installation tool,
rustup
, available on the Rust website. - Create a Rust Project: Use Cargo, Rust’s package manager, to create a new project:
cargo new rust_ml_project
.
Choosing a Machine Learning Library
Rust offers several libraries for machine learning, such as tch-rs
, rusty-machine
, and linfa
. For our example, we'll use rusty-machine
.
Adding Dependencies
Update your Cargo.toml
with the necessary dependencies:
[dependencies]
rusty-machine = "0.5.4"
rulinalg = "0.4.2"