Book Image

Natural Language Understanding with Python

By : Deborah A. Dahl
5 (1)
Book Image

Natural Language Understanding with Python

5 (1)
By: Deborah A. Dahl

Overview of this book

Natural Language Understanding facilitates the organization and structuring of language allowing computer systems to effectively process textual information for various practical applications. Natural Language Understanding with Python will help you explore practical techniques for harnessing NLU to create diverse applications. with step-by-step explanations of essential concepts and practical examples, you’ll begin by learning about NLU and its applications. You’ll then explore a wide range of current NLU techniques and their most appropriate use-case. In the process, you’ll be introduced to the most useful Python NLU libraries. Not only will you learn the basics of NLU, you’ll also discover practical issues such as acquiring data, evaluating systems, and deploying NLU applications along with their solutions. The book is a comprehensive guide that’ll help you explore techniques and resources that can be used for different applications in the future. By the end of this book, you’ll be well-versed with the concepts of natural language understanding, deep learning, and large language models (LLMs) for building various AI-based applications.
Table of Contents (21 chapters)
1
Part 1: Getting Started with Natural Language Understanding Technology
4
Part 2:Developing and Testing Natural Language Understanding Systems
16
Part 3: Systems in Action – Applying Natural Language Understanding at Scale

Summary

In this chapter, we covered the major development tools and Python libraries that are used in NLP application development. We discussed the JupyterLab development environment and the GitHub software repository system. The major libraries that we covered were NLTK, spaCy, and Keras. Although this is by no means an exhaustive list of NLP libraries, it’s sufficient to get a start on almost any NLP project.

We covered installation and basic usage for the major libraries, and we provided some suggested tips on selecting libraries. We summarized some useful auxiliary packages, and we concluded with a simple example of how the libraries can be used to do some NLP tasks.

The topics discussed in this chapter have given you a basic understanding of the most useful Python packages for NLP, which you will be using for the rest of the book. In addition, the discussion in this chapter has given you a start on understanding the principles for selecting tools for future projects...