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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

Combining everything together

In this section, we will combine everything we have illustrated so far and create a classifier for the iris dataset.

Getting ready

The iris dataset is described in more detail in the Working with data sources recipe in Chapter 1, Getting Started with TensorFlow. We will load this data and make a simple binary classifier to predict whether a flower is the species Iris setosa or not. To be clear, this dataset has three species, but we will only predict whether a flower is a single species, I. setosa or not, giving us a binary classifier. We will start by loading the libraries and data, then transform the target accordingly.

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