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TensorFlow Machine Learning Cookbook

You're reading from   TensorFlow Machine Learning Cookbook Over 60 recipes to build intelligent machine learning systems with the power of Python

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Product type Paperback
Published in Aug 2018
Publisher Packt
ISBN-13 9781789131680
Length 422 pages
Edition 2nd Edition
Languages
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Authors (2):
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Sujit Pal Sujit Pal
Author Profile Icon Sujit Pal
Sujit Pal
Nick McClure Nick McClure
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Nick McClure
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Toc

Table of Contents (13) Chapters Close

Preface 1. Getting Started with TensorFlow FREE CHAPTER 2. The TensorFlow Way 3. Linear Regression 4. Support Vector Machines 5. Nearest-Neighbor Methods 6. Neural Networks 7. Natural Language Processing 8. Convolutional Neural Networks 9. Recurrent Neural Networks 10. Taking TensorFlow to Production 11. More with TensorFlow 12. Other Books You May Enjoy

Implementing RNN for spam prediction

To start, we will apply the standard RNN unit to predict a singular numerical output, a probability of being spam.

Getting ready

In this recipe, we will implement a standard RNN in TensorFlow to predict whether or not a text message is spam or ham. We will use the SMS spam-collection dataset from the ML repository at UCI. The architecture we will use for prediction will be an input RNN sequence from embedded text, and we will take the last RNN output as a prediction of spam or ham (1 or 0).

How to do it...

  1. We start by loading the libraries...
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