Natural Language Processing using R Pocket Primer

✍ Scribed by Oswald Campesato

Publisher: Pocket Primer
Year: 2024
Tongue: English
Leaves: 266
Category: Library

No coin nor oath required. For personal study only.

✦ Synopsis

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. Companion files with source code and figures are included and available for downloading by emailing the publisher at [email protected] with proof of purchase. FEATURES: Covers extensive topics related to natural language processing using R Features companion files with source code and figures from the book

✦ Table of Contents

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

📜 SIMILAR VOLUMES

Natural language processing using very l

📁 Natural language processing using very large corpora

✍ H. Feldweg (auth.), Susan Armstrong, Kenneth Church, Pierre Isabelle, Sandra Man 📂 Library 📅 1999 🏛 Springer Netherlands 🌐 English

<p>ABOUT THIS BOOK This book is intended for researchers who want to keep abreast of cur rent developments in corpus-based natural language processing. It is not meant as an introduction to this field; for readers who need one, several entry-level texts are available, including those of (Church and

Natural Language Processing Using Very L

📁 Natural Language Processing Using Very Large Corpora

✍ H. Feldweg (auth.), Susan Armstrong, Kenneth Church, Pierre Isabelle, Sandra Man 📂 Library 📅 1999 🏛 Springer Netherlands 🌐 English

Approach to natural language processing

📁 Approach to natural language processing using rules

✍ Kazimierczak. 📂 Library 🌐 English

Natural Language Processing Practical us

📁 Natural Language Processing Practical using Transformers with Python

✍ Tony Snake 📂 Library 📅 2022 🏛 Independently published 🌐 English

Learn how you can perform named entity recognition using HuggingFace Transformers and spaCy libraries in Python. Named Entity Recognition (NER) is a typical natural language processing (NLP) task that automatically identifies and recognizes predefined entities in a given text. Entities like person n

Supertagging: Using Complex Lexical Desc

📁 Supertagging: Using Complex Lexical Descriptions in Natural Language Processing

✍ Srinivas Bangalore, Aravind K. Joshi (eds.) 📂 Library 📅 2010 🏛 The MIT Press 🌐 English

Investigations into employing statistical approaches with linguistically motivated representations and its impact on Natural Language processing tasks. The last decade has seen computational implementations of large hand-crafted natural language grammars in formal frameworks such as Tree-Adjoinin

Natural Language Processing of Semitic L

📁 Natural Language Processing of Semitic Languages

✍ Imed Zitouni (eds.) 📂 Library 📅 2014 🏛 Springer-Verlag Berlin Heidelberg 🌐 English

<p><p>Research in Natural Language Processing (NLP) has rapidly advanced in recent years, resulting in exciting algorithms for sophisticated processing of text and speech in various languages. Much of this work focuses on English; in this book we address another group of interesting and challenging