In this chapter, we saw how to use character-based CNN, by training a model to search for duplicate pairs. Character CNN gives us the flexibility to train models with unknown characters, and it is more generic than word-level embedding. Similar kinds of networks can be used for searching, matching, and deduplication.

In the next chapter, we will learn how to train a model for Named Entity Recognition (NER) using LSTM.