Advanced Deep Learning with Python

Summary

This was the first chapter devoted to NLP. Appropriately, we started with the basic building blocks of most NLP algorithms today—the words and their context-based vector representations. We started with n-grams and the need to represent words as vectors. Then, we discussed the word2vec, fastText, and GloVe models. Finally, we implemented a simple pipeline to train an embedding model and we visualized word vectors with t-SNE.

In the next chapter, we'll discuss RNNs—a neural network architecture that naturally lends itself to NLP tasks.