In this chapter, we will take a step further into exploring the TensorFlow library and how it can be leveraged to solve complex tasks. In particular, you will build a neural network that generates a new (non-existing) chapter of a book by learning patterns from the existing chapters. In addition, you will grasp more of the TensorFlow functionalities, such as saving/restoring a model, and so on.
This chapter will also introduce a new and more powerful recurrent neural network model called the gated recurrent unit (GRU). You will learn how it works and why we are choosing it over the simple RNN.
In summary, the topics of the chapter include the following:
- Why use the GRU network? You will learn how the GRU network works, what problems it solves, and what its benefits are.
- Generating your book chapter—you will go step by step...