# 🌍 Africa CO₂ Emission Predictor
A machine learning web application that predicts COâ‚‚ emissions across African countries based on historical climate data. The project combines a **FastAPI backend** for prediction and data handling with an **interactive frontend dashboard** for visualization.
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## đź“‹ Table of Contents
- Project Overview
- Features
- Demo
- Technologies Used
- Project Structure
- Installation & Setup
- API Documentation
- Usage
- Model Training
- Future Improvements
- Contributing
- License
- Contact
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## đź§ Project Overview
**Africa COâ‚‚ Predictor** is an environmental analysis tool that enables users to:
- **Analyze** historical COâ‚‚ emission data across 6 African countries
- **Predict** future emissions (2030) using machine learning
- **Visualize** trends through interactive charts
- **Track** climate indicators (temperature, energy use, GDP, population)
- **Switch** between light and dark themes
- **Access** from any device (fully responsive)
This tool supports environmental analysis and policy planning efforts in Africa by making COâ‚‚ emission forecasting accessible and visual.
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## ✨ Features
- **Predictive Analytics** - ML-powered COâ‚‚ emission predictions
- **Interactive Visualizations** - Line and bar charts using Chart.js
- **Historical Data** - Complete dataset from 2000-2020
- **Country Comparison** - Side-by-side emission comparisons
- **Custom Predictions** - Manual input for custom scenarios
- **Dark Mode** - Eye-friendly dark theme with glassmorphism
- **Responsive Design** - Works on desktop, tablet, and mobile
- **Real-time Updates** - Instant prediction results
- **RESTful API** - Well-documented FastAPI endpoints
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### Quick Start
```bash
# Clone the repository
git clone
github.com
# Navigate to backend
cd africa-co2-predictor/backend
# Install dependencies
pip install -r requirements.txt
# Run the server
uvicorn app:app --reload
```
Then open `frontend/index.ht …