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TensorFlow Machine Learning Cookbook by Nick McClure

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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.

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 ...

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