NeuRythmia

A python package to work with EEG data in machine learning applications.
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Table of Contents

1. About The Project
   • Built With
2. Getting Started
   • Prerequisites
   • Installation
3. Usage
4. Roadmap
5. Contributing
6. License
7. Contact
8. Acknowledgments

About The Project

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

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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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