Metadata-Version: 2.1
Name: evolutionary-keras
Version: 2.0
Summary: UNKNOWN
Home-page: https://github.com/N3PDF/evolutionary_keras
Author: S. Carrazza, J. Cruz-Martinez, Roy Stegeman
Author-email: juan.cruz@mi.infn.it, roy.stegeman@mi.infn.it
License: UNKNOWN
Platform: UNKNOWN
Classifier: Programming Language :: Python
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Physics
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Requires-Python: >=3.6
Description-Content-Type: text/markdown
Requires-Dist: numpy
Requires-Dist: cma
Requires-Dist: tensorflow (>2.1*)
Provides-Extra: docs
Requires-Dist: sphinx-rtd-theme ; extra == 'docs'
Requires-Dist: recommonmark ; extra == 'docs'

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[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.3630399.svg)](https://doi.org/10.5281/zenodo.3630399)



# evolutionary_keras

Keras is one of the most widely used Machine Learning frameworks available in the market. It is a high-level API written in Python and that can run on mulitple backends. Their goal is to be able to build and test new model as fast as possible.

Keras models are trained through the usage of optimizers, all of which are Gradient Descent based. This module deals with that shortcoming of Keras by implementing several Evolutionary Algorithms on top of Keras while keeping the main philosophy of the project: it must be easy to prototype.

The default project library now provides support for:
- Nodal Genetical Algorithm (NGA)
- Covariance Matrix Adaptation Evolution Strategy (CMA-ES)


