Summary

We reviewed a few selected real-world use cases in this chapter to demonstrate the breadth and depth of the techniques that we have learned about in this book. We trust this chapter has inspired you with new ideas, motivated you to invent new applications, and showed you how to apply the code examples that we have included in this book.

NLP keeps evolving at an unprecedented speed. ChatGPT, CPT-4, Llama 2.0, and so on were all developed in 2023. It is foreseeable that more and more generative AI models will emerge. With the knowledge in this book, you will be able to transition to generative NLP. This book helped you familiarize yourself with the fundamentals of NLP, including concepts such as tokenization, part-of-speech tagging, named entity recognition, syntactic parsing, LSA, LDA, and BERTopic. These techniques form the basis for your journey into generative NLP. Generative NLP heavily relies on neural networks. This book also presented the basics of neural network architectures...