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🚗 Used Cars Price Prediction

A Flask-based web application that predicts the resale price of used cars based on features such as manufacturing year, kilometers driven, company, and fuel type. The app uses a trained machine learning model to provide accurate predictions through a simple and user-friendly web interface.

📌 Features

✅ Predicts used car prices based on input parameters

✅ Flask backend with machine learning integration

✅ Input validation and error handling

✅ REST API endpoint (/predict) for JSON-based predictions

✅ Simple, responsive frontend using HTML (index.html)

🛠️ Tech Stack

Python 3.x

Flask – Web framework

NumPy – Numerical computations

Pickle – Model serialization

HTML/CSS/JS – Frontend UI

📂 Project Structure Used-Car-Price-Prediction/ │ ├── static/ # Static files (CSS, JS, images) ├── templates/ # HTML templates (frontend UI) │ └── index.html │ ├── car_price_model.pkl # Trained ML model (serialized) ├── app.py # Main Flask application ├── requirements.txt # Required dependencies └── README.md # Project documentation

⚙️ Installation & Setup

Clone the repository

git clone https://github.com/your-username/used-car-price-prediction.git cd used-car-price-prediction

Create & activate virtual environment (optional but recommended)

python -m venv venv source venv/bin/activate # Linux/Mac venv\Scripts\activate # Windows

Install dependencies

pip install -r requirements.txt

Run the application

python app.py

Access the app in your browser

http://127.0.0.1:5000/

📊 Usage

Open the app in your browser.

Enter the required details:

Year of the car

Kilometers Driven

Company (as encoded value)

Fuel Type (as encoded value)

Click Predict.

The app will display the predicted car price.

🔌 API Endpoint POST /predict

Request (Form Data):

{ "year": 2018, "kms_driven": 45000, "company": 2, "fuel_type": 1 }

Response (JSON):

{ "price": 450000.75 }

Error Example:

{ "error": "All fields are required. Please fill in all values." }

📦 Dependencies

Add these to requirements.txt:

Flask numpy pickle-mixin

🚀 Deployment

You can deploy this app on:

Heroku

PythonAnywhere

Render

AWS / Azure / GCP

📜 License

This project is licensed under the MIT License.

👨‍💻 Author

Anuj Kumar 📧 [email protected]

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