n the previous chapter, we used classic machine learning techniques to build our text classifiers. In this chapter, we will replace those with deep learning techniques via the use of recurrent neural networks (RNN).
In particular, we will use a relatively simple bidirectional LSTM model. If this is new to you, keep reading – if not, please feel free to skip ahead!
The dataset attribute of the batch variable should point to the trn variable of the torchtext.data.TabularData type. This is a useful checkpoint to understand how data flow differs in training deep learning models.
Let's begin by touching upon the overhyped terms, that is, deep in deep learning and neural in deep neural networks. Before we do that, let's take a moment to explain why I use PyTorch and compare it to Tensorflow and Keras—the other popular deep learning frameworks...
