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House Price Prediction Web App

Overview

This project is a web application for predicting house prices using an XGBoost regression model. Users can input various features, such as median income, house age, average rooms, average bedrooms, population, average occupation, latitude, and longitude, to get a predicted house price.

Table of Contents

Getting Started

Prerequisites

Before you begin, ensure you have the following prerequisites installed:

  • Python 3.x
  • pip (Python package installer)

Installation

  1. Clone the repository:

    git clone https://github.com/your-username/house-price-web-app.git

Usage

Run the streamlit web app

streamlit run app.py

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