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NeuRythmia

A python package to work with EEG data in machine learning applications.
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View Demo · Report Bug · Request Feature

Table of Contents
  1. About The Project
  2. Getting Started
  3. Usage
  4. Roadmap
  5. Contributing
  6. License
  7. Contact
  8. Acknowledgments

About The Project

NeuRythmia Screen Shot

This package is a collection of utilities to work with EEG data in machine learning applications. It is built on top of various other packages like Numpy, MNE, Tensorflow, etc. It provides a simple interface to perform various operations on EEG data. The package is still in development and will be updated.

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Built With

  • Matplotlib
  • NumPy
  • scikit-learn

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Getting Started

Installation

  1. Clone the repo
    git clone https://github.com/adityaprakash-work/NeuRythmia.git
  2. pip
    pip install git+https://github.com/adityaprakash-work/NeuRythmia.git

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Usage

Common Imports

import neurythmia as nr

For more examples, please refer to the Documentation

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Roadmap

See the open issues for a full list of proposed features (and known issues).

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Contributing

Contributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.

If you have a suggestion that would make this better, please fork the repo and create a pull request. You can also simply open an issue with the tag "enhancement". Don't forget to give the project a star! Thanks again!

  1. Fork the Project
  2. Create your Feature Branch (git checkout -b feature/AmazingFeature)
  3. Commit your Changes (git commit -m 'Add some AmazingFeature')
  4. Push to the Branch (git push main feature/AmazingFeature)
  5. Open a Pull Request

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License

Distributed under the Apache 2.0 License. See LICENSE for more information.

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Contact

Aditya Prakash
Twitter - @adityaprakash_t
Email - [email protected]

Project Link: https://github.com/adityaprakash-work/NeuRythmia

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