Natural Language Processing and Computational Linguistics

Summary

In the previous chapter we introduced our readers to deep learning for text, and in this chapter, we saw how we can leverage the power of deep learning in our own applications, whether we use Keras or spaCy. Knowing how to assign sentiment scores or classify our documents gives us a huge boost when designing intelligent text systems, and with pretrained models, we don't have to perform heavy computations every time we wish to make such a classification. It is now within our capacity to build a strong and varied text analysis pipeline!

In the next chapter, we will discuss two popular text analysis problems—sentiment analysis and building our own chatbot—and what possible approaches we can take to solve these problems.