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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
Author Profile Icon Nick McClure
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

Neural Networks

In this chapter, we will introduce neural networks and how to implement them in TensorFlow. Most of the subsequent chapters will be based on neural networks, so learning how to use them in TensorFlow is very important. We will start by introducing the basic concepts of neural networking before working up to multilayer networks. In the last section, we will create a neural network that will learn how to play Tic Tac Toe.

In this chapter, we'll cover the following recipes:

  • Implementing operational gates
  • Working with gates and activation functions
  • Implementing a one-layer neural network
  • Implementing different layers
  • Using multilayer networks
  • Improving predictions of linear models
  • Learning to play Tic Tac Toe

The reader can find all of the code from this chapter online, at https://github.com/nfmcclure/tensorflow_cookbook and at the Packt repository: https:/...

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