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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

Using a multilayer neural network

We will now apply our knowledge of different layers to real data by using a multilayer neural network on the low birth weight dataset.

Getting ready

Now that we know how to create neural networks and work with layers, we will apply this methodology with the aim of predicting the birth weight in the low birth weight dataset. We'll create a neural network with three hidden layers. The low birth weight dataset includes the actual birth weight and an indicator variable for whether the birth weight is above or below 2,500 grams. In this example, we'll make the target the actual birth weight (regression) and then see what the accuracy is on the classification at the end. At the end, our...

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