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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

Layering nested operations

In this recipe, we will learn how to put multiple operations on the same computational graph.

Getting ready

It's important to know how to chain operations together. This will set up layered operations in the computational graph. For a demonstration, we will multiply a placeholder by two matrices and then perform addition. We will feed in two matrices in the form of a three-dimensional NumPy array:

import tensorflow as tf 
sess = tf.Session() 

How to do it...

It is also important to note how the data will change shape as it passes through...

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