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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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Nick McClure Nick McClure
Author Profile Icon Nick McClure
Nick McClure
Sujit Pal Sujit Pal
Author Profile Icon Sujit Pal
Sujit Pal
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Toc

Table of Contents (19) Chapters Close

Title Page
Copyright and Credits
Dedication
Packt Upsell
Contributors
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 1. Other Books You May Enjoy Index

Using TensorFlow Serving


In this section, we will show you how to set up your RNN model to predict spam or ham text messages on TensorFlow. We will first illustrate how to save a model in a protobuf format, and will then load the model into a local server, listening on port 9000 for input.

Getting ready

We start this section by encouraging reader to read through the official documentation and the short tutorials on the TensorFlow Serving site available at https://www.tensorflow.org/serving/serving_basic.

For this example, we will reuse most of the RNN code we used in the on Predicting Spam with RNNs recipe in Chapter 9Recurrent Neural Networks. We will alter our model saving code to save a protobuf model in the correct folder structure that is necessary to use TensorFlow Serving.

Note

Note that all scripts in this chapter should be executed from the command line bash prompt.

For the updated installation instructions, visit the official installation site at: https://www.tensorflow.org/serving...

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