Recurrent Neural Network with Keras

Recurrent Neural Networks (RNN) initially created in the 1980's are a powerful and robust type of neural network in which output from the previous step are fed as input to the current step. The most important feature of RNN is Hidden state and they have memory which remembers each and every information through time. In Recurrent neural networks, we use the result obtained through the hidden layers to process future input as shown in the diagram below. Keras is a very powerful open source Python library which is runs on top of top of other open source machine libraries like TensorFlow, Theano etc, used for developing and evaluating deep learning models and leverages various optimization techniques. In this project we will train a sequence (math expression) to sequence recurrent neural network to implement/solve simple mathematical operations by creating, training and evaluating a simple recurrent neural network model.