House Price Detection using Machine Learning

This is a repository that demonstrates how to predict house prices using machine learning. We use the Scikit-Learn library to build a predictive model.

Prerequisites

Before you start, make sure you have the following libraries installed:

numpy: NumPy is the fundamental package for scientific computing in Python. matplotlib: Matplotlib is a plotting library for the Python programming language. scikit-learn: Scikit-Learn is a machine learning library for Python. StandardScaler: StandardScaler is used for feature scaling in machine learning. You can install these libraries using pip:

pip install numpy matplotlib scikit-learn

Data

The data used for this project should be placed in the data directory. Make sure to organize your data appropriately before running the script.

Features

House Price Prediction: The script uses a machine learning model to predict house prices based on the provided data.

Getting Started

To get started with this project, follow these steps:

1. Clone the repository to your local machine:

   https://github.com/MuhammadBilal0111/House-Price-Predictions-Using-Machine-Learning-.git

2. Navigate to the project directory:

   cd House-Price-Predictions-Using-Machine-Learning-

3. Open the project in your code editor and start working on your improvements or modifications.
4. After making changes, add and commit your code:

   git add .

   git commit -m "Add your descriptive commit message here"

6. Push your changes to your remote repository (e.g., GitHub):

   git push origin main

Contributors

Muhammad Bilal

m.bilal0111@gmail.com

Acknowledgments

This project uses the Scikit-Learn library for machine learning. Special thanks to the open-source community for providing essential tools and libraries. Feel free to customize this README according to your project's specifics.