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TensorFlow Machine Learning Cookbook

You're reading from   TensorFlow Machine Learning Cookbook Over 60 practical recipes to help you master Google's TensorFlow machine learning library

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Product type Paperback
Published in Feb 2017
Publisher Packt
ISBN-13 9781786462169
Length 370 pages
Edition 1st Edition
Languages
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Author (1):
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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 2. The TensorFlow Way FREE CHAPTER 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 Index

Introduction


Up to this point, we have only considered machine learning algorithms that mostly operate on numerical inputs. If we want to use text, we must find a way to convert the text into numbers. There are many ways to do this and we will explore a few common ways this is achieved.

If we consider the sentence TensorFlow makes machine learning easy, we could convert the words to numbers in the order that we observe them. This would make the sentence become 1 2 3 4 5. Then when we see a new sentence, machine learning is easy, we can translate this as 3 4 0 5, denoting words we haven't seen with an index of zero. With these two examples, we have limited our vocabulary to six numbers. With large texts, we can choose how many words we want to keep, and usually keep the most frequent words, labeling everything else with the index of zero.

If the word learning has a numerical value of 4, and the word makes has a numerical value of 2, then it would be natural to assume that learning is twice...

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