In this chapter, we have seen all the details related to the rule-based system and how the rule-based approach helps us to develop rapid prototypes for complex problems with high accuracy. We have seen the architecture of the rule-based system. We have learned about the advantages, disadvantages, and challenges for the rule-based system. We have seen how this system is helpful to us for developing NLP applications such as grammar correction systems, chatbots, and so on. We have also discussed the recent trends for the rule-based system.
In the next chapter, we will learn the other main approaches called machine learning, to solve NLP applications. The upcoming chapter will give you all the details about which machine learning algorithms you need to use for developing NLP applications. We will see supervised ML, semi-supervised ML, and unsupervised ML techniques. We will...