Getting started with Rust

🛠️ Build

To build the project:

cargo build

To run a specific example:

cargo run --bin <file_name_without_rs>

🤖 Machine Learning

• Linear Regression using SVD – Linear regression implemented from scratch using Singular Value Decomposition.
• K-means – (in progress) Unsupervised clustering using centroids and Euclidean distance.

🧰 Utilities

• Euclidean Distance – Basic implementation of $\ell_2$ norm between two vectors.
• CSV Reading – Simple CSV parsing with csv and serde.
• 2D Plotting – Visualizing functions and model outputs using plotly.
• Linear Algebra with nalgebra – Matrix and vector operations using the nalgebra crate.
• Linear Algebra with ndarray – Alternative linear algebra toolkit closer to NumPy-style arrays.

📁 Project Structure

This repository is organized with one file per experiment or module inside src/bin/. Each file is a standalone binary crate meant for hands-on learning and testing.