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.