Once text data has been converted into numerical features using the NLP techniques discussed in the previous sections, text classification works just like any other classification task.
In this section, we will apply these preprocessing technique to news articles, product reviews, and Twitter data and teach you about various classifiers to predict discrete news categories, review scores, and sentiment polarity.
First, we will introduce the Naive Bayes model, a probabilistic classification algorithm that works well with the text features produced by a bag-of-words model.
The code samples for this section are in the text_classification notebook.
