Quick Start
Introduction

Models & Functions

Neural Network - Model
Architecture Layers - Model
Data - Model
Activation - Functions
Loss - Functions

Layers

Embedding layer (Input)
Fully Connected (Dense)
Recurrent Neural Network (RNN)
Long Short-Term Memory (LSTM)
Gated Recurrent Unit (GRU)
Convolution 2D (CNN)
Pooling (CNN)
Dropout - Regularization
Flatten - Adapter

Examples and more

Data preparation - Examples
Network training - Examples
Expert Documentation
Appendix

EpyNN

»
Data preparation - Examples
View page source

Data preparation - Examples

_images/python_dataTypes-01.png

Boolean

Dummy dataset

String

Dummy dataset
Protein Modification

Numerical (Series)

Dummy dataset
Music Authorship

Numerical (Image)

Dummy dataset
MNIST Database

Previous Next

© Copyright 2021, Florian Malard and Stéphanie Olivier-Van Stichelen.

Built with Sphinx using a theme provided by Read the Docs.