🚗 Car Price Prediction using Flask and Decision Tree Regressor

This project is a simple machine learning-powered web application to predict car prices based on user inputs such as fuel type, engine type, engine size, and horsepower. The application is built with Flask, uses scikit-learn's DecisionTreeRegressor, and provides both USD and INR price predictions.

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🔧 Technologies Used

• Python 3
• Flask (Web Framework)
• Pandas (Data Handling)
• Scikit-learn (ML Model)
• Joblib (Model Persistence)
• Bootstrap 5 (Frontend Styling)

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📂 Project Structure

Car-Price-Prediction/
│
├── app.py                # Main Flask Application
├── car.csv                # Training Data (Features & Target)
├── model.joblib           # Saved Machine Learning Model
├── requirements.txt       # Project Dependencies
├── templates/
│   └── car.html           # HTML Template for Frontend
└── static/                # (Optional) For static files like CSS, JS, images

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🚀 Features

✅ Predicts Car Price (USD) and Car Price (INR) ✅ User-friendly Bootstrap-based Interface ✅ Persistent trained model using Joblib (no retraining on every request) ✅ Production-ready Flask app structure

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📊 Dataset (car.csv)

The car.csv contains synthetic or real-world data with the following columns:

Fuel Type	Engine Type	Engine Size	Horsepower	Price (USD)
0 / 1	0 / 1	float	float	float

• Fuel Type: 0 = Petrol, 1 = Diesel
• Engine Type: 0 = Manual, 1 = Automatic

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🔥 Running Locally

1️⃣ Clone Repository

git clone https://github.com/lovnishverma/Car-Price-Prediction.git
cd Car-Price-Prediction

2️⃣ Install Dependencies

pip install -r requirements.txt

3️⃣ Run the Application

python app.py

Visit http://localhost:5000

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🏭 Running in Production

For production deployments, use Gunicorn:

gunicorn -w 4 -b 0.0.0.0:5000 app:app

Or deploy on Render / Railway / Huggingface using this requirements.txt.

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💡 Example Usage

Input Field	Sample Value
Fuel Type	0
Engine Type	1
Engine Size	1.6
Horsepower	120

Output: Predicted Price (USD): $18,000 Predicted Price (INR): ₹1,47,6720

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🌐 Live Demo

View on Render

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📥 Requirements

Flask==3.0.3
pandas==2.2.2
scikit-learn==1.5.0
joblib==1.4.2

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📄 License

This project is open-source under the MIT License.

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✨ Author

Lovnish Verma Portfolio Website GitHub

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