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Python Deep Learning Cookbook

You're reading from   Python Deep Learning Cookbook Over 75 practical recipes on neural network modeling, reinforcement learning, and transfer learning using Python

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Product type Paperback
Published in Oct 2017
Publisher Packt
ISBN-13 9781787125193
Length 330 pages
Edition 1st Edition
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Author (1):
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Indra den Bakker Indra den Bakker
Author Profile Icon Indra den Bakker
Indra den Bakker
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Toc

Table of Contents (15) Chapters Close

Preface 1. Programming Environments, GPU Computing, Cloud Solutions, and Deep Learning Frameworks 2. Feed-Forward Neural Networks FREE CHAPTER 3. Convolutional Neural Networks 4. Recurrent Neural Networks 5. Reinforcement Learning 6. Generative Adversarial Networks 7. Computer Vision 8. Natural Language Processing 9. Speech Recognition and Video Analysis 10. Time Series and Structured Data 11. Game Playing Agents and Robotics 12. Hyperparameter Selection, Tuning, and Neural Network Learning 13. Network Internals 14. Pretrained Models

Translating sentences

Another application of deep learning in text has got its boost in performance and popularity thanks to a couple of large search engines. Translating sentences is a hard task because each language has its own rules, exceptions, and expressions. What we tend to forget is that the translation of words often largely depends on the context around it. Some believe that solving a language thoroughly can be a huge milestone for achieving general AI, because intelligence and language are well connected and small nuances in language can be crucial to understanding.

In our next recipe, we will demonstrate how to use a sequence-to-sequence model to translate sentences from English to French. We will be using the CNTK framework. 

How to do it...

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