Educational python for Neural Networks

EpyNN is written in pure Python/NumPy.

If you use EpyNN in academia, please cite:

Malard F., Danner L., Rouzies E., Meyer J. G., Lescop E., Olivier-Van Stichelen S. EpyNN: Educational python for Neural Networks, 2021, Submitted.

Documentation

Please visit https://epynn.net/ for extensive documentation.

Purpose

EpyNN is intended for teachers, students, scientists, or more generally anyone with minimal skills in Python programming who wish to understand and build from basic implementations of Neural Network architectures.

Although EpyNN can be used for production, it is meant to be a library of homogeneous architecture templates and practical examples which is expected to save an important amount of time for people who wish to learn, teach or develop from scratch.

Content

EpyNN features scalable, minimalistic and homogeneous implementations of major Neural Network architectures in pure Python/Numpy including:

Model and

 

 

 

To finish reading, please visit source site