Boston House Price Prediction

This project is a web application that predicts house prices in Boston using machine learning. It is based on the famous Boston Housing dataset, which contains various features related to housing prices in different neighborhoods in Boston.

Table of Contents

• Description
• Installation
• Usage
• Features
• Technologies
• Contributing
• License

Description

The Boston House Price Prediction project provides a user-friendly web interface where users can input various features of a property, such as crime rate, average number of rooms, and more. The application utilizes a machine learning model trained on the Boston Housing dataset to predict the house price based on the provided features.

Installation

To run the project locally, follow these steps:

1. Clone the repository:

git clone https://github.com/your-username/boston-house-price-prediction.git
cd boston-house-price-prediction

Install the required dependencies:

pip install -r requirements.txt

Run the Flask application:

python app.py

The web application will be accessible at http://localhost:5000/.

Usage

Open your web browser and navigate to http://localhost:5000/.

Enter the required input features in the form.

Click the "Predict" button to get the predicted house price.

Features

• Predict house prices in Boston based on input features.
• User-friendly web interface for easy input and prediction.
• Well-trained machine learning model for accurate predictions.

Technologies

• Python
• Flask
• HTML
• CSS
• JavaScript
• scikit-learn

Contributing

Contributions to the project are welcome! If you find any bugs or want to add new features, feel free to open an issue or submit a pull request.

License

This project is licensed under the MIT License. See the LICENSE file for details.