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

Identifying problems that are the appropriate level of difficulty for the technology

Note

This chapter is focused on technical considerations. Questions such as whether a market exists for a proposed application, or how to decide whether customers will find it appealing, are important questions, but they are outside of the scope of this book.

Here are some kinds of problems that are a good fit for the state of the art.

Today’s NLU is very good at handling problems based on specific, concrete topics, such as these examples:

  • Classifying customers’ product reviews into positive and negative reviews: Online sellers typically offer buyers a chance to review products they have bought, which is helpful for other prospective buyers as well as for sellers. But large online retailers with thousands of products are then faced with the problem of what to do with the information from thousands of reviews. It’s impossible for human tabulators to read all the...