# Recurrent Neural Network (RNN) Model Training System

(Redirected from Recurrent Neural Network Training System)

A Recurrent Neural Network (RNN) Model Training System is a neural network training system that implements an RNN algorithm to solve an RNN training task.

**Context:**- It can range from being a Uni-Directional RNN Training System to being a Bi-Directional RNN Training System.

**Example(s):**- an LSTM Training System.
- an RNN-based Language Model Trainer.
- a Keras-based one. [1]

**Counter-Example(s):****See:**TensorFlow RNN.

## References

### 2017

- https://github.com/fchollet/keras/blob/master/README.md
- QUOTE: Keras is a high-level neural networks API, written in Python and capable of running on top of either TensorFlow[2] or Theano[3]. It was developed with a focus on enabling fast experimentation. Being able to go from idea to result with the least possible delay is key to doing good research.
Use Keras if you need a deep learning library that:

- Supports both convolutional networks and recurrent networks, as well as combinations of the two.

- QUOTE: Keras is a high-level neural networks API, written in Python and capable of running on top of either TensorFlow[2] or Theano[3]. It was developed with a focus on enabling fast experimentation. Being able to go from idea to result with the least possible delay is key to doing good research.

### 2015

- https://github.com/dennybritz/rnn-tutorial-rnnlm/blob/master/RNNLM.ipynb
- QUOTE: Recurrent Neural Networks Tutorial, Part 2 – Implementing a Language Model RNN with Python, Numpy and Theano