In this chapter, we will introduce you to working with text in TensorFlow. We will start by introducing how word embeddings work using the bag-of-words method, and then we will move on to implementing more advanced embeddings such as word2vec and doc2vec.
In this chapter, we will be covering the following topics:
- 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 will find all of the code for this chapter online at https://github.com/nfmcclure/tensorflow_cookbook and at the Packt repository: https://github.com/PacktPublishing/TensorFlow-Machine-Learning-Cookbook-Second-Edition ...
