 Название: Natural Language Processing using R Pocket Primer
Автор: Oswald Campesato
Издательство: Mercury Learning and Information
Год: 2022
Страниц: 266
Язык: английский
Формат: pdf (true), epub, mobi
Размер: 10.1 MB
This book is for developers who are looking for an overview of basic concepts in Natural Language Processing using R. 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 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.
You will be exposed to various NLP and Machine Learning topics in this book, some of which are presented in a cursory manner for two reasons. First, it’s important that you be exposed to these concepts. In some cases, you will find topics that might pique your interest, and hence motivate you to learn more about them through self-study; in other cases, you will probably be satisfied with a brief introduction. Hence, you can decide whether to delve into more detail regarding the topics in this book.
Second, a full treatment of all the topics that are covered in this book would probably triple its page count, and few people are interested in reading long technical books. Hence, this book provides a decent view of the NLP and Machine Learning landscape, based on the belief that this approach will be more beneficial for readers who are experienced developers who want to learn about NLP and Machine Learning.
The Chapter 7 is devoted to NLP and modern architectures that support NLP-based tasks. Specifically, you will learn about the transformer architecture, the pre-trained BERT model and its variants, and features of GPT-2 and GPT-3 from OpenAI. Please note that this chapter contains Python-based code samples. The rationale for the inclusion of Python code is simple: you can quickly find a vast set of blog posts, articles, code samples, and Github repositories regarding BERT, the Transformer architecture, and GPT-3 via a simple Internet search. Fortunately, most of the code samples are short and involve rudimentary Python constructs, which you can learn from a plethora of free online resources.
Features:
- Covers extensive topics related to natural language processing using R
- Features companion files with source code and figures from the book
The Target Audience:
This book is intended primarily for people who have a solid background as software developers. Specifically, this book is for developers who are accustomed to searching online for more detailed information about technical topics. If you are a beginner, there are other books that are more suitable for you, and you can find them by performing an online search.
This book is also intended to reach an international audience of readers with highly diverse backgrounds in various age groups. This book uses standard English rather than colloquial expressions that might be confusing to those readers. People learn in different ways, which includes reading, writing, or hearing new material. This book tries to take these approaches into consideration to provide a comfortable and meaningful learning experience for the intended readers.
Contents:
Preface
Chapter 1: Introduction to R
Chapter 2: Loops, Conditional Logic, and Dataframes
Chapter 3: Working with Functions in R
Chapter 4: NLP Concepts (I)
Chapter 5: NLP Concepts (II)
Chapter 6: NLP in R
Chapter 7: Transformer, BERT, and GPT
Appendix: Intro to Probability and Statistics
Index
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