Natural Language Processing Fundamentals for Developers

Written for developers, this guide offers a survey of the foundational ideas in natural language processing. Its scope is intentionally broad, covering many different methods, and it is aimed at readers whose technical experience varies widely. Throughout, the material is supported by a large number of code examples and listings.

The book opens with the handling of data, focusing on the aspects that matter most for NLP work. Two chapters then introduce core NLP concepts, followed by two chapters that use Python code to demonstrate those ideas in practice.

A sixth chapter turns to applications, including sentiment analysis, recommender systems, an analysis of COVID-19 data, spam detection, and a brief look at chatbots. The final chapter covers the Transformer architecture, BERT-based models, and the GPT family, which the author describes as recent developments from the past three years and as the current state of the art.

Two appendices provide introductory material on regular expressions and on probability and statistics, both with Python examples. Companion files containing source code and figures are available to readers who provide proof of an Amazon purchase by emailing info@merclearning.com.