Implementing RNN for spam prediction

To start, we will apply the standard RNN unit to predict a singular numerical output, a probability of being spam.

Getting ready

In this recipe, we will implement a standard RNN in TensorFlow to predict whether or not a text message is spam or ham. We will use the SMS spam-collection dataset from the ML repository at UCI. The architecture we will use for prediction will be an input RNN sequence from embedded text, and we will take the last RNN output as a prediction of spam or ham (1 or 0).

How to do it...

1. We start by loading the libraries...