🚗 AI Used Car Price Prediction
A Machine Learning powered web application that predicts the estimated market value of a used car based on its specifications — brand, model, age, mileage, fuel type, engine, and more.
🔗 Live App: ai-used-car-price-prediction.streamlit.app
📌 Overview
This project uses a Random Forest Regressor trained on 15,000+ used car listings to estimate a fair market price for a vehicle. Users enter details like brand, fuel type, transmission, mileage, and engine capacity through an interactive dashboard, and the model returns an instant price prediction.
✨ Features
- 🎯 Instant price prediction based on 12+ car attributes
- 🎨 Clean, modern, dashboard-style UI
- ☁️ Model hosted on Hugging Face Hub (downloaded at runtime)
- 📊 Trained on real-world used car listing data
- 🔒 Input validation to prevent incomplete predictions
🛠️ Tech Stack
| Layer | Technology |
|---|---|
| Frontend / UI | Streamlit |
| ML Model | scikit-learn (Random Forest Regressor) |
| Data Handling | pandas |
| Model Storage | Hugging Face Hub |
| Deployment | Streamlit Community Cloud |
🚀 Getting Started (Run Locally)
# Clone the repository
git clone https://github.com/Malik7343/AI-Used-Car-Price-Prediction.git
cd AI-Used-Car-Price-Prediction
# Create a virtual environment
python -m venv .venv
.venv\Scripts\activate # Windows
# source .venv/bin/activate # macOS/Linux
# Install dependencies
pip install -r requirements.txt
# Run the app
streamlit run app.py
The app will open automatically in your browser at http://localhost:8501.
📂 Project Structure
AI-Used-Car-Price-Prediction/
├── app.py # Main Streamlit application
├── requirements.txt # Python dependencies
├── backend/
│ └── models/ # (model downloaded here at runtime)
├── utils/ # Helper utilities
└── README.md
🧠 Model Inputs
| Feature | Description |
|---|---|
| Car Name | Name/variant of the car |
| Brand | Manufacturer (e.g. Maruti, Hyundai) |
| Model | Model year |
| Vehicle Age | Age of the car in years |
| KM Driven | Total kilometers driven |
| Seller Type | Individual / Dealer / Trustmark Dealer |
| Fuel Type | Petrol / Diesel / CNG / LPG / Electric |
| Transmission | Manual / Automatic |
| Mileage | Fuel efficiency (km/l) |
| Engine | Engine displacement (CC) |
| Max Power | Maximum power output (bhp) |
| Seats | Number of seats |
📈 Model Performance
- Accuracy: ~89.4%
- Algorithm: Random Forest Regressor
- Training Data: 15,000+ used car listings
🙋 Author
Malik Taj Khan GitHub
📄 License
This project is open source and available for educational purposes.
