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Predict house prices using XGBoost regression. This project preprocesses data, trains the model, and evaluates predictions to forecast house prices based on various features.

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House Price Prediction using XGBoost Regression

Introduction

This project predicts house prices using the XGBoost regression algorithm. The code is implemented in a Google Colab notebook for convenience.

Usage

Steps to Use:

  1. Clone the Repository:

    • Clone the repository to your local machine if you want to run the notebook locally:
      git clone https://github.com/VIKRAM2563/House-Price-Prediction.git
      cd House-Price-Prediction
  2. Open the Notebook:

    • Open the Google Colab notebook directly from the repository link.
  3. Run the Notebook:

    • Follow the instructions within the notebook to execute each cell.

Model

  • Algorithm: XGBoost regression.
  • Steps: Data preprocessing, model training, evaluation.

Results

  • Model performance metrics, such as RMSE, will be displayed in the notebook.

Contributing

  • Contributions are welcome! Submit pull requests for improvements or bug fixes.

Contact

For any inquiries or feedback, please contact Vikram P at vikrampartha24@gmail.com.

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Predict house prices using XGBoost regression. This project preprocesses data, trains the model, and evaluates predictions to forecast house prices based on various features.

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