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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 backpropagation

One of the benefits of using TensorFlow is that it can keep track of operations and automatically update model variables based on back propagation. In this recipe, we will introduce how to use this aspect to our advantage when training machine learning models.

Getting ready

Now, we will introduce how to change our variables in the model in such a way that a loss function is minimized. We have learned how to use objects and operations, and create loss functions that will measure the distance between our predictions and targets. Now, we just have to tell TensorFlow how to back propagate errors through our computational graph to update the variables and minimize the loss function. This is done via...

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