Book Image

Recurrent Neural Networks with Python Quick Start Guide

By : Simeon Kostadinov
Book Image

Recurrent Neural Networks with Python Quick Start Guide

By: Simeon Kostadinov

Overview of this book

Developers struggle to find an easy-to-follow learning resource for implementing Recurrent Neural Network (RNN) models. RNNs are the state-of-the-art model in deep learning for dealing with sequential data. From language translation to generating captions for an image, RNNs are used to continuously improve results. This book will teach you the fundamentals of RNNs, with example applications in Python and the TensorFlow library. The examples are accompanied by the right combination of theoretical knowledge and real-world implementations of concepts to build a solid foundation of neural network modeling. Your journey starts with the simplest RNN model, where you can grasp the fundamentals. The book then builds on this by proposing more advanced and complex algorithms. We use them to explain how a typical state-of-the-art RNN model works. From generating text to building a language translator, we show how some of today's most powerful AI applications work under the hood. After reading the book, you will be confident with the fundamentals of RNNs, and be ready to pursue further study, along with developing skills in this exciting field.
Table of Contents (8 chapters)

Generating Your Own Book Chapter

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 chapteryou will go step by step...