Summary

In this chapter, we learned about the motivations behind converting human language in the form of text into vectors. This helps machine learning algorithms to execute mathematical functions on the text, detect patterns in language, and gain an understanding of the meaning of the text. We also saw different types of vector representation techniques, such as character-level encoding and one-hot encoding.

In the next chapter, we will look at the areas of text paraphrasing, summarization, and generation. We will see how we can automate the process of text summarization using the NLP techniques we have learned so far.