pyrenn is a recurrent neural network toolbox for Python and Matlab.
- pyrenn allows to create a wide range of (recurrent) neural network configurations
- It is very easy to create, train and use neural networks
- It uses the Levenberg–Marquardt algorithm (a second-order Quasi-Newton optimization method) for training, which is much faster than first-order methods like gradient descent. In the matlab version additionally the Broyden–Fletcher–Goldfarb–Shanno algorithm is implemented
- The python version is written in pure python and numpy and the matlab version in pure matlab (no toolboxes needed)
- Real-Time Recurrent Learning (RTRL) algorithm and Backpropagation Through Time (BPTT) algorithm are implemented and can be used to implement further training algorithms
- It comes with various examples which show how to create, train and use the neural network
- download or clone (with git) this repository to a directory of your choice.
- Run the given examples in the
examplesfolder. - Read the documenation and create your own neural network
Copyright (C) 2016 Dennis Atabay
This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.
This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.
You should have received a copy of the GNU General Public License along with this program. If not, see http://www.gnu.org/licenses/