Recurrent Neural Networks with Python Quick Start Guide
- Paperback: 122 pages
- Publisher: WOW! eBook (November 30, 2018)
- Language: English
- ISBN-10: 1789132339
- ISBN-13: 978-1789132335
Recurrent Neural Networks with Python Quick Start Guide: Learn how to develop intelligent applications with sequential learning and apply modern methods for language modeling with neural network architectures for deep learning with Python’s most popular TensorFlow framework
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 Recurrent Neural Networks with Python Quick Start Guide 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.