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 book chapter

After going through the theoretical part of this chapter, we are ready to dive into coding. I hope you grasp the fundamental behind the GRU model and will feel comfortable seeing the notations in the TensorFlow program. It consists of five parts, most of which may be familiar to you from Chapter 2, Building Your First RNN with TensorFlow:

  • Obtaining the book text: this one is really straightforward. Your task is to assure a lot of plain text is ready for training. 
  • Encoding the text: this one can be challenging, since we need to accommodate the encoding with the proper dimensions. Sometimes, this operation can take more time than expected but it is a requirement for compiling the program flawlessly. There are different types of encoding algorithms and we will choose a fairly simple one so you fully understand its true essence.
  • Building the TensorFlow...