Summary

In this chapter, we learned about the basics of NLP and how it differs from text analytics. We covered the various preprocessing steps that are included in NLP, such as tokenization, PoS tagging, stemming, lemmatization, and more. We also looked at the different phases an NLP project has to pass through, from data collection to model deployment.

In the next chapter, you will learn about the different methods of extracting features from unstructured text, such as TF-IDF and bag of words. You will also learn about NLP tasks such as tokenization, lemmatization, and stemming in more detail. Furthermore, text visualization techniques such as word clouds will be introduced.