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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 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 Index

Chapter 7. Natural Language Processing

Here we will cover an introduction to working with text in TensorFlow. We start by introducing how word embeddings work and using the bag of words method, then we move on to implementing more advanced embeddings such as Word2vec and Doc2vec:

  • Working with bag of words
  • Implementing TF-IDF
  • Working with Skip-gram Embeddings
  • Working with CBOW Embeddings
  • Making Predictions with Word2vec
  • Using Doc2vec for Sentiment Analysis

As a note, the reader may find all the code for this chapter online at https://github.com/nfmcclure/tensorflow_cookbook.

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