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Kaggle-Works is your one-stop repo to organize every phase of a Kaggle competition or tabular-data project. It enforces a clear directory layout so you never lose track of files, and makes it easy to hand off or reproduce your work later.

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🏆 Kaggle-Works

A personal hub to organize every phase of your Kaggle journeys—from raw data to polished submissions.


📖 Overview

Kaggle-Works enforces a clean, reproducible workflow for tabular-data competitions:

  • Competition-Submits/
    Store your CSV/JSON submissions and keep a history of top leaderboard runs.
  • Zipped-Data/
    Untouched archive downloads (ZIP, TAR, etc.)—your “source-of-truth.”
  • Extracted-Data/
    Unpacked & lightly cleaned CSV/Parquet files ready for analysis.
  • My_Works/
    Jupyter notebooks, Python scripts, utility modules, write-ups, and visualizations.

Whether you’re chasing that gold medal or simply honing your data chops, this repo structure helps you stay organized and shareable.


🚀 Getting Started

  1. Clone the repo
    git clone https://github.com/Kratugautam99/Kaggle-Works.git
    cd Kaggle-Works
  2. Install dependencies
    Create a virtual environment and install your favorite libs:
    python3 -m venv .venv
    source .venv/bin/activate
    pip install -r requirements.txt
  3. Add raw data archives
    Drop your .zip/.tar files into Zipped-Data/.
  4. Unpack & clean
    Extract into Extracted-Data/ and run your preprocessing pipelines (in My_Works/).
  5. Train & submit
    Develop models in My_Works/, save final submission.csv under Competition-Submits/.

🔍 Directory Structure

Kaggle-Works/
├── Competition-Submits/   ← Final submission files
├── Zipped-Data/           ← Raw dataset archives
├── Extracted-Data/        ← Unpacked & cleaned data
└── My_Works/              ← Notebooks, scripts, analyses

💡 Usage Tips

  • Keep raw data immutable in Zipped-Data/.
  • Version your cleaned exports in Extracted-Data/.
  • Isolate EDA & experiments in My_Works/.
  • Never overwrite prior submissions—store each attempt in Competition-Submits/.

🤝 Contributing

Feel free to fork, propose improvements, or share new templates:

  1. Fork the repo
  2. Create a feature branch (git checkout -b feature/my-awesome-pipeline)
  3. Commit your changes (git commit -m "Add my new data-cleaning recipe")
  4. Push to your branch (git push origin feature/my-awesome-pipeline)
  5. Open a Pull Request

📜 License

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

About

Kaggle-Works is your one-stop repo to organize every phase of a Kaggle competition or tabular-data project. It enforces a clear directory layout so you never lose track of files, and makes it easy to hand off or reproduce your work later.

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