logo

EbookBell.com

Most ebook files are in PDF format, so you can easily read them using various software such as Foxit Reader or directly on the Google Chrome browser.
Some ebook files are released by publishers in other formats such as .awz, .mobi, .epub, .fb2, etc. You may need to install specific software to read these formats on mobile/PC, such as Calibre.

Please read the tutorial at this link:  https://ebookbell.com/faq 


We offer FREE conversion to the popular formats you request; however, this may take some time. Therefore, right after payment, please email us, and we will try to provide the service as quickly as possible.


For some exceptional file formats or broken links (if any), please refrain from opening any disputes. Instead, email us first, and we will try to assist within a maximum of 6 hours.

EbookBell Team

Text Mining With R 1st Edition Julia Silge David Robinson

  • SKU: BELL-55540346
Text Mining With R 1st Edition Julia Silge David Robinson
$ 31.00 $ 45.00 (-31%)

4.3

78 reviews

Text Mining With R 1st Edition Julia Silge David Robinson instant download after payment.

Publisher: O'Reilly Media
File Extension: PDF
File size: 9.74 MB
Pages: 150
Author: Julia Silge, David Robinson
ISBN: 9781491981658, 1491981652
Language: English
Year: 2017
Edition: 1

Product desciption

Text Mining With R 1st Edition Julia Silge David Robinson by Julia Silge, David Robinson 9781491981658, 1491981652 instant download after payment.

Tackle a variety of tasks in natural language processing by learning how to use the R language and tidy data principles. This practical guide provides examples and resources to help you get up to speed with dplyr, broom, ggplot2, and other tidy tools from the R ecosystem. You’ll discover how tidy data principles can make text mining easier, more effective, and consistent by employing tools already in wide use. Text Mining with R shows you how to manipulate, summarize, and visualize the characteristics of text, sentiment analysis, tf-idf, and topic modeling. Along with tidy data methods, you’ll also examine several beginning-to-end tidy text analyses on data sources from Twitter to NASA datasets. These analyses bring together multiple text mining approaches covered in the book. Get real-world examples for implementing text mining using tidy R package Understand natural language processing concepts like sentiment analysis, tf-idf, and topic modeling Learn how to analyze unstructured, text-heavy data using R language and ecosystem

Related Products