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

Selecting NLP approaches

NLP can be done with a wide variety of possible techniques. When you get started on an NLP application, you have many choices to make, which are affected by a large number of factors. One of the most important factors is the type of application itself and the information that the system needs to extract from the data to perform the intended task. The next section addresses how the application affects the choice of techniques.

Fitting the approach to the task

Recall from Chapter 1, that there are many different types of NLP applications divided into interactive and non-interactive applications. The type of application you choose will play an important role in choosing the technologies that will be applied to the task. Another way of categorizing applications is in terms of the level of detail required to extract the needed information from the document. At the coarsest level of analysis (for example, classifying documents into two different categories...