Summary
This chapter provided a landscape view of the NLP topics covered in this book. We learned that the development of NLP was due to the success of NLU and NLG. Then, we surveyed the NLP techniques that are covered by Gensim. The main techniques include BoW, TF-IDF, LSA/LSI, Word2Vec, Doc2Vec, LDA, and Ensemble LDA. We were also introduced to BERTopic modeling. We then learned about the other two popular NLP Python libraries, spaCy and NLTK.
As we all know, a computer operates on zeros and ones but cannot comprehend the great works of Shakespeare. So, how do ChatGPT and other language models understand language? The very first step is to convert words to numerical values. The next chapter will teach you about text representation.
