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Your go-to solution for tracking and validating machine learning models for scientific research

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OpenMLHub: Machine Learning Model Tracking and Validation

Overview

Welcome to the OpenMLHub Client – your go-to solution for tracking and validating machine learning models for scientific research. This project facilitates seamless integration with OpenMLHub, enabling you to manage and assess your models efficiently.

Features

  • Model Tracking: Easily track the performance of your machine learning models over time.
  • Validation Support: Streamline the validation process for scientific research purposes.
  • OpenMLHub Integration: Connect and collaborate with the OpenMLHub community effortlessly.
  • User-Friendly Interface: Intuitive design for a smooth user experience.
  • Scalable Architecture: Built for scalability to accommodate various project sizes.

Getting Started

Follow these steps to get started with the OpenMLHub Client:

  1. Installation:

    pip install openmlhub
    
  2. Configuration:

    • Obtain your OpenMLHub API key.
    • Set up your configuration file with the API key.
  3. Usage:

    import os
    from openmlhub import make_logger
    from openmlhub.config import OpenMLHubConf('<user_id>', 'api_key')
    
    api_key = os.environ['OPENMLHUB_API_KEY']
    logger = make_logger(OpenMLHubConf('<user_id>', api_key), '<model_id>')
    logger.log()

Examples

TBC

Contributing

We welcome contributions to enhance the OpenMLHub Client. To contribute:

  1. Fork the repository.
  2. Create a new branch: git checkout -b feature/your-feature.
  3. Commit your changes: git commit -m 'Add your feature'.
  4. Push to the branch: git push origin feature/your-feature.
  5. Open a pull request.

License

This project is licensed under the MIT License.

Contact

For any inquiries or support, contact us at support@openmlhubclient.com.

Happy modeling and tracking! 🚀

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Your go-to solution for tracking and validating machine learning models for scientific research

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