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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 an address matching example

Now that we have measured numerical and text distances, we will spend some time learning how to combine them to measure distances between observations that have both text and numerical features.

Getting ready

Nearest-neighbor is a great algorithm to use for address matching. Address matching is a type of record matching in which we have addresses in multiple datasets and would like to match them up. In address matching, we may have typos in the address, different cities, or different ZIP Codes, but they may all refer to the same address. Using the nearest-neighbor algorithm across the numerical and character components of an address may help us to identify addresses that are actually the same...

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