Summary

In this chapter, we learned different techniques to represent text data in deep learning. We learned how to use pretrained word embeddings and our own trained embeddings when working on a different domain. We built a text classifier using LSTMs and one-dimensional convolutions.

In the next chapter, we will learn how to train deep learning algorithms to generate stylish images, and new images, and to generate text.