Machine translation is often done using so-called statistical machine translation, based on statistical models. This approach works very well, but a key issue is that, for every pair of languages, we need to rebuild the architecture. Thankfully, in 2014, Cho et al. (https://arxiv.org/pdf/1406.1078.pdf) came out with a paper that aims to solve this, and other problems, using the increasingly popular recurrent neural networks. The model is called sequence-to-sequence, and has the ability to be trained on any pair of languages by just providing the right amount of data. In addition, its power lies in its ability to match sequences of different lengths, such as in machine translation, where a sentence in English may have a different size when compared to a sentence in Spanish. Let's examine how these tasks...
Recurrent Neural Networks with Python Quick Start Guide
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Recurrent Neural Networks with Python Quick Start Guide
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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.
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Recurrent Neural Networks with Python Quick Start Guide
Table of Contents (8 chapters)
Preface
Free Chapter
Introducing Recurrent Neural Networks
Building Your First RNN with TensorFlow
Generating Your Own Book Chapter
Creating a Spanish-to-English Translator
Building Your Personal Assistant
Improving Your RNN Performance
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