Getting Started

Getting Started

This repository contains a collection of Rust AI examples demonstrating various machine learning, deep learning, and natural language processing techniques.

Prerequisites

• Rust (latest stable version)
• Cargo (comes with Rust)

Running Examples

Each example is a standalone Cargo project located in the examples/ directory.

# Navigate to an example directory
cd examples/<example-name>

# Run the example
cargo run

Available Examples

Example	Category	Status	Requires
Text Classification	NLP	✅ Runnable	Local models/ BERT checkpoint
Sentiment Analysis	NLP	✅ Runnable	Internet (first run downloads model)
Language Detection	NLP	✅ Runnable	data/languages.json
Keyword Extraction	NLP	✅ Runnable	.txt files in documents/
Email Spam Classification	NLP	⚠️ Incomplete	Assets only; no source code yet
KNN Classifier	ML	✅ Runnable	data/iris.csv
Decision Tree Classifier	ML	✅ Runnable	data/loans.csv
House Price Prediction	ML	✅ Runnable	data/house.csv
Image Classification	DL	✅ Runnable	Internet (first run downloads model) + an image
OCR	DL	⚠️ Incomplete	No fn main; inference not implemented

Note

Each example page contains its own Project Structure, Dataset Format, and a line-by-line code walkthrough. Start from the Project Overview for the overall layout.

Adding your own data

Most examples read a fixed path relative to their own directory, so the simplest way to try your own data is to replace the committed file (keeping the same columns). Model-based examples either use a committed models/ directory or download it on first run.

Documentation

This documentation site is built with Astro Starlight. To run it locally:

# Install dependencies
npm install

# Start development server
npm run dev

# Build for production
npm run build

# Preview production build
npm run preview