Summary

In this chapter, we have explored applications of NNs to document classification in NLP. We covered the basic concepts of NNs, reviewed a simple MLP, and applied it to a binary classification problem. We also provided some suggestions for improving performance by modifying hyperparameters and tuning. Finally, we discussed the more advanced types of NNs—RNNs and CNNs.

In Chapter 11, we will cover the currently best-performing techniques in NLP—transformers and pretrained models.