Natural Language Processing Fundamentals for Developers

This book is for developers who are looking for an overview of basic concepts in Natural Language Processing. It casts a wide net of techniques to help developers who have a range of technical backgrounds. Numerous code samples and listings are included to support myriad topics. The first chapter shows you various details of managing data that are relevant for NLP. The next pair of chapters contain NLP concepts, followed by another pair of chapters with Python code samples to illustrate those NLP concepts. Chapter 6 explores applications, e.g., sentiment analysis, recommender systems, COVID-19 analysis, spam detection, and a short discussion regarding chatbots. The final chapter presents the Transformer architecture, BERT-based models, and the GPT family of models, all of which were developed during the past three years and considered SOTA (“state of the art”). The appendices contain introductory material (including Python code samples) on regular expressions and probability/statistical concepts. Companion files with source code and figures are included.

FEATURES:

Covers extensive topics related to natural language processing  Includes separate appendices on regular expressions and probability/statistics Features companion files with source code and figures from the book.
1: Working with Data
2: NLP Concepts (I)
3: NLP Concepts (II)
4. Algorithms and Toolkits (I)
5. Algorithms and Toolkits (II)
6: NLP Applications
7: Transformer, BERT, and GPT
Appendices:
A: Introduction to Regular Expressions
B: Introduction to Probability and Statistics