🏠 House Price Prediction

Welcome to the House Price Prediction project repository! This project aims to predict house prices using a machine learning model trained on data. It covers essential stages such as data preprocessing, feature engineering, model selection, and evaluation.

👨‍💻 Team Members

• Md Ali Akbar Sami
• Sakib Chowdhury
• Zarin Tasnima Azad

📁 Project Structure

• .ipynb_checkpoints - Jupyter notebook checkpoints (auto-generated)
• data - Dataset folder containing the data required for the project
• myenv - Virtual environment containing all required libraries and dependencies
• HousePricePrediction.ipynb - Jupyter notebook with the code and analysis

🚀 Getting Started

Follow the steps below to get started with the project. The virtual environment myenv contains all necessary libraries, including Jupyter, so no additional installations are needed.

1. Clone the Repository

git clone https://github.com/akbarsami22/HousePricePrediction.git

2. Change Directory

cd HousePricePrediction

3. Activate the Virtual Environment

The virtual environment myenv is preconfigured with all the dependencies. To activate it, run the following command based on your operating system:

• For Windows:

  cd myenv/Scripts
  activate
  cd..
  cd..

• For Linux/Mac:

  source myenv/bin/activate

4. Launch the Jupyter Notebook

Once the environment is activated, you can directly launch the Jupyter Notebook with the following command:

jupyter notebook HousePricePrediction.ipynb

🔍 Project Overview

This project focuses on predicting house prices based on various features such as square footage, number of bedrooms, number of bathrooms, and location. Key components of the workflow include:

• Data preprocessing (cleaning, handling missing data, and outliers)
• Feature engineering (using MEstimate encoding for categorical variables)
• Model selection and training
• Model evaluation using R²

📊 Dataset

The dataset required for this project is already available in the data folder. You don't need to download it separately.

💻 Dependencies

All required dependencies are included in the myenv virtual environment, so there’s no need for additional installation.

🤝 Contributions

Contributions are welcome! Feel free to fork this repository, create a new branch, and submit a pull request. Whether it's improving the model, adding new features, or fixing bugs, your contribution is highly appreciated.

📜 License

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

📧 Contact

If you have any questions or suggestions, feel free to reach out to any of the team members.