Text mining with R: a tidy approach (Record no. 3390)

MARC details
000 -LEADER
fixed length control field 02068nam a22002177a 4500
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20220920145012.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
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020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9789352135769
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 519.502855133
Item number SIL
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name Silge, Julia
245 ## - TITLE STATEMENT
Title Text mining with R: a tidy approach
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Name of publisher, distributor, etc. O'Reilly Media
Place of publication, distribution, etc. Mumbai
Date of publication, distribution, etc. 2021
300 ## - PHYSICAL DESCRIPTION
Extent xii, 178 p.
365 ## - TRADE PRICE
Price type code INR
Price amount 675.00
520 ## - SUMMARY, ETC.
Summary, etc. All Indian Reprints of O'Reilly are printed in Grayscale.<br/><br/>"Much of the data available today is unstructured and text-heavy, making it challenging for analysts to apply their usual data wrangling and visualization tools. with this practical book, you’ll explore text-mining techniques with tidy text, a package that authors Julia Silge and David Robinson developed using the tidy principles behind R packages like graph and dplyr. You’ll learn how tidy text and other tidy tools in R can make text analysis easier and more effective.<br/><br/>The authors demonstrate how treating text as data frames enables you to manipulate, summarize and visualize characteristics of text. You’ll also learn how to integrate natural language processing (NLP) into effective workflows. Practical code examples and data explorations will help you generate real insights from literature, news and social media.<br/><br/>Learn how to apply the tidy text format to NLP<br/>Use sentiment analysis to mine the emotional content of text<br/>Identify a document’s most important terms with frequency measurements<br/>Explore relationships and connections between words with the graph and widyr packages<br/>Convert back and forth between R’s tidy and non-tidy text formats<br/>Use topic modeling to classify document collections into natural groups<br/>Examine case studies that compare Twitter archives, dig into NASA metadata and analyze thousands of Usenet messages
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Data mining
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element R (Computer program language)
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Natural language processing (Computer science)
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Discourse analysis--Data processing
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme Dewey Decimal Classification
Koha item type Book
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Collection code Bill No Bill Date Home library Current library Shelving location Date acquired Source of acquisition Cost, normal purchase price Total Checkouts Full call number Accession Number Date last seen Date checked out Copy number Cost, replacement price Price effective from Koha item type
    Dewey Decimal Classification     IT & Decisions Sciences TB1415 08-09-2022 Indian Institute of Management LRC Indian Institute of Management LRC General Stacks 09/20/2022 Technical Bureau India Pvt. Ltd. 472.50 1 519.502855133 SIL 003146 09/19/2023 07/27/2023 1 675.00 09/20/2022 Book

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