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πŸš— 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.


πŸ”§ Technologies Used

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

πŸ“‚ Project Structure

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

πŸš€ Features

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


πŸ“Š 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

πŸ”₯ 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


🏭 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.


πŸ’‘ 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): β‚Ή1,47,6720


🌐 Live Demo

View on Render


πŸ“₯ Requirements

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

πŸ“„ License

This project is open-source under the MIT License.


✨ Author

Lovnish Verma Portfolio Website GitHub