Summary

We have finished this chapter about a very hot NLP topic – text classification. In this chapter, you first learned about text classification concepts such as binary classification, multilabel classification, and multiclass classification. Next, you learned how to train TextCategorizer, spaCy's text classifier component. You learned how to transform your data into spaCy training format and then train the TextCategorizer component with this data.

After learning text classification with spaCy's TextCategorizer, in the final section, you learned how to combine spaCy code and Keras code. First, you learned the basics of neural networks, including some handy layers such as the dense layer, dropout layer, embedding layer, and recurrent layers. Then, you learned how to tokenize and preprocess the data with Keras' Tokenizer.

You had a quick review of sequential modeling with LSTMs, as well as recalling word vectors from Chapter 5, Working with Word Vectors...