In this section, we will start by showing you how to work with a bag-of-words embedding in TensorFlow. This mapping is what we introduced in the introduction. Here, we will show you how to use this type of embedding for spam prediction.
Working with bag-of-words embeddings
Getting ready
To illustrate how to use bag-of-words with a text dataset, we will use a spam-ham phone text database from the UCI machine learning data repository (https://archive.ics.uci.edu/ml/datasets/SMS+Spam+Collection). This is a collection of phone text messages that are spam or not-spam (ham). We will download this data, store it for future use, and then proceed with the bag-of-words method to predict if a text is spam or not. The model that will...