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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
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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

Implementing TF-IDF

Since we can choose the embedding for each word, we might decide to change the weighting on certain words. One such strategy is to up weight useful words and downweight overly common or rare words. The embedding we will explore in this recipe is an attempt to achieve this.

Getting ready

TF-IDF is an acronym that stands for Text Frequency - Inverse Document Frequency. This term is essentially the product of text frequency and inverse document frequency for each word.

In the preceding recipe, we introduced the bag-of-words methodology, which assigned a value of 1 for every occurrence of a word in a sentence. This is probably not ideal as each category of sentence (spam and ham in the preceding recipe&apos...

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