Metadata-Version: 2.4
Name: echoes
Version: 1.0.1
Summary: Machine Learning with Echo State Networks in Python
Author-email: Fabrizio Damicelli <fabridamicelli@gmail.com>
License-Expression: MIT
Project-URL: Changelog, https://github.com/fabridamicelli/echoes/blob/main/CHANGELOG.md
Project-URL: Repository, https://github.com/fabridamicelli/echoes
Project-URL: Documentation, https://fabridamicelli.github.io/echoes
Keywords: python,machine-learning,shallow-learning,neural-networks,recurrent-neural-networks,reservoir-computing,echo-state-network
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Developers
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Requires-Python: >=3.9
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: numpy>=1.23.5
Requires-Dist: scikit-learn>=1.2.0
Requires-Dist: pandas>=1.0.3
Requires-Dist: matplotlib>=3.2.0
Requires-Dist: seaborn>=0.10.1
Requires-Dist: numba>=0.56.4
Dynamic: license-file

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# echoes 

- 🤖 Machine learning with Echo State Networks(ESN)
- 🧱 High level API, `scikit-learn` compatible API, eg `fit-predict` interface 
- ⚡️ Fast! (Thanks to numba ✨)


## Installation and quick start
```bash
pip install echoes
```

See [Documentation](https://fabridamicelli.github.io/echoes/) and [example notebooks](https://github.com/fabridamicelli/echoes/tree/master/examples/notebooks).

## Feedback
Any bugs, suggestions, problems? Just [open an issue!](https://github.com/fabridamicelli/echoes/issues/new)

## Citing
If you find echoes useful for a publication, then please use the following BibTeX to cite it:

```
@misc{echoes,
  author = {Damicelli, Fabrizio},
  title = {echoes: Echo State Networks with Python},
  year = {2019},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/fabridamicelli/echoes}},
}
```

## Tests 
Run tests with 
```bash
make test
```

## References
  - [Reservoir computing approaches to recurrent neural network training, Mantas & Jaeger, 2009](https://www.sciencedirect.com/science/article/pii/S1574013709000173)
  - [A Practical Guide to Applying Echo State Networks, Mantas, 2012](https://link.springer.com/chapter/10.1007/978-3-642-35289-8_36)
  - [Echo state network (scholarpedia), Jaeger](http://www.scholarpedia.org/article/Echo_state_network)
  - [Short Term Memory in Echo State Networks, Jaeger, 2001](http://publica.fraunhofer.de/eprints/urn_nbn_de_0011-b-731310.pdf)
