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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

Implementing elastic net regression

Elastic net regression is a type of regression that combines lasso regression with ridge regression by adding L1 and L2 regularization terms to the loss function.

Getting ready

Implementing elastic net regression should be straightforward after the previous two recipes, so we will implement this in multiple linear regression on the iris dataset, instead of sticking to the two-dimensional data as before. We will use petal length, petal width, and sepal width to predict sepal length.

How to do it...

We proceed with the recipe as follows...

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