This concludes our look at RNNs. In this chapter, we first discussed the general principles of RNNs, and then saw how to acquire and prepare some text for use by a model, noting that it is straightforward to use an alternative source of text here. We then saw how to create and instantiate our model. We then trained our model and used it produce text from our starting string, noting that the network has learned that words are units of text and how to spell quite a variety of words, somewhat in the style of the author of the text, with only a couple of non-words.
In the next chapter, we will look at the use of TensorFlow Hub, which is a software library.
