Further processing options

Supervised machine learning for text analysis in R

"Text data is important for many domains, from healthcare to marketing to the digital humanities, but specialized approaches are necessary to create features for machine learning from language. Supervised Machine Learning for Text Analysis in R explains how to preprocess text data for modeling,...

Full Description

Bibliographic Details
Authors and Corporations: Hvitfeldt, Emil (Author), Silge, Julia (Author)
Other Authors: Silge, Julia (VerfasserIn)
Edition: First edition
Type of Resource: Book
Language: English
published:
Boca Raton, London, New York CRC Press, Taylor & Francis Group 2022
Series: Data science series
A Chapman & Hall book
Subjects:
Source: Verbunddaten SWB
Subject: DK 681.3.06
DK 519.23
DK 519.25
QH 234
QH 500
QH 234
Call number: 22.1574 8.
ISBN: 9780367554187
9780367554194
0367554194
0367554186
Description
Summary: "Text data is important for many domains, from healthcare to marketing to the digital humanities, but specialized approaches are necessary to create features for machine learning from language. Supervised Machine Learning for Text Analysis in R explains how to preprocess text data for modeling, train models, and evaluate model performance using tools from the tidyverse and tidymodels ecosystem. Models like these can be used to make predictions for new observations, to understand what natural language features or characteristics contribute to differences in the output, and more. If you are already familiar with the basics of predictive modeling, use the comprehensive, detailed examples in this book to extend your skills to the domain of natural language processing"--
Item Description: Literaturverzeichnis: Seite 369-378
Physical Description: xix, 381 Seiten; Diagramme
ISBN: 9780367554187
9780367554194
0367554194
0367554186
Call number: 22.1574 8.