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TensorFlow 1.x Deep Learning Cookbook

You're reading from   TensorFlow 1.x Deep Learning Cookbook Over 90 unique recipes to solve artificial-intelligence driven problems with Python

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Product type Paperback
Published in Dec 2017
Publisher Packt
ISBN-13 9781788293594
Length 536 pages
Edition 1st Edition
Languages
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Authors (2):
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Dr. Amita Kapoor Dr. Amita Kapoor
Author Profile Icon Dr. Amita Kapoor
Dr. Amita Kapoor
Antonio Gulli Antonio Gulli
Author Profile Icon Antonio Gulli
Antonio Gulli
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Toc

Table of Contents (15) Chapters Close

Preface 1. TensorFlow - An Introduction FREE CHAPTER 2. Regression 3. Neural Networks - Perceptron 4. Convolutional Neural Networks 5. Advanced Convolutional Neural Networks 6. Recurrent Neural Networks 7. Unsupervised Learning 8. Autoencoders 9. Reinforcement Learning 10. Mobile Computation 11. Generative Models and CapsNet 12. Distributed TensorFlow and Cloud Deep Learning 13. Learning to Learn with AutoML (Meta-Learning) 14. TensorFlow Processing Units

Learning to write as Shakespeare with RNNs

In this recipe, we will learn how to generate text similar to that written by William Shakespeare. The key idea is very simple: we take as input a real text written by Shakespeare and we give it as input to an RNN which will learn the sequences. This learning is then used to generate new text which looks like that written by the greatest writer in the English language.

For the sake of simplicity, we will use the framework TFLearn (http://tflearn.org/), which runs on top of TensorFlow. This example is part of the standard distribution and it is available at https://github.com/tflearn/tflearn/blob/master/examples/nlp/lstm_generator_shakespeare.py . The model developed one is an RNN character-level language model where the sequences considered are sequences of characters and not words.
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