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

Taking maintenance costs into account

The final consideration for natural language applications, especially deployed applications, is the cost of maintenance. This is easy to overlook because NLU applications have several maintenance considerations that don’t apply to most traditional applications. Specifically, the type of language used in some applications changes over time. This is expected since it reflects changes in the things that the users are talking about. In customer service applications, for example, product names, store locations, and services change, sometimes very quickly. The new vocabulary that customers use to ask about this information changes as well. This means that new words have to be added to the system, and machine learning models have to be retrained.

Similarly, applications that provide rapidly changing information need to be kept up to date on an ongoing basis. As an example, the word COVID-19 was introduced in early 2020 – no one had ever...