Skip to content

Latest commit

 

History

History
33 lines (20 loc) · 1.2 KB

README.md

File metadata and controls

33 lines (20 loc) · 1.2 KB
Raw

House Price Prediction Project

This project is a task from my internship at Prodigy Infotech, focused on machine learning using linear regression to predict house prices. The dataset and challenge are from Kaggle's House Prices: Advanced Regression Techniques competition.

Technologies Used

  • Python
  • Pandas
  • Scikit-learn
  • Matplotlib

Files Included

  • house_price_prediction.ipynb: Jupyter notebook containing the code.
  • submission.csv: Submission file for Kaggle competition.

Dataset

The dataset used is from Kaggle's competition, accessible at the House Prices competition overview.

Setup and Usage

  1. Clone the repository.
  2. Open house_price_prediction.ipynb in Jupyter Notebook or any compatible environment.
  3. Run the notebook to see the predictions and explore the code.

Contributing

Contributions are not typically expected for internship tasks, but feel free to fork the repository and modify the code for learning purposes.

License

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