Learning Resource and Development

Data science, analytics and machine learning with R / (Record no. 30237)

MARC details
000 -LEADER
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001 - CONTROL NUMBER
control field 23306575
003 - CONTROL NUMBER IDENTIFIER
control field CSPC
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20250908120505.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 230905t20232023enka b 001 0 eng d
010 ## - LIBRARY OF CONGRESS CONTROL NUMBER
LC control number 2023279268
015 ## - NATIONAL BIBLIOGRAPHY NUMBER
National bibliography number GBC285151
Source bnb
016 7# - NATIONAL BIBLIOGRAPHIC AGENCY CONTROL NUMBER
Record control number 020584938
Source Uk
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9780128242711
Qualifying information (pbk)
035 ## - SYSTEM CONTROL NUMBER
System control number 23306575
035 ## - SYSTEM CONTROL NUMBER
System control number (OCoLC)1286790517
040 ## - CATALOGING SOURCE
Original cataloging agency YDX
Language of cataloging eng
Description conventions rda
Transcribing agency YDX
Modifying agency BDX
-- UKMGB
-- OCLCF
-- SISPL
-- CTL
-- FIE
-- DLC
-- CSPC
042 ## - AUTHENTICATION CODE
Authentication code lccopycat
050 00 - LIBRARY OF CONGRESS CALL NUMBER
Classification number HF1008
Item number .F38 2023
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 658.05631
Item number F278d
Edition number 23
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Fávero, Luiz Paulo,
Relator term author.
245 10 - TITLE STATEMENT
Title Data science, analytics and machine learning with R /
Statement of responsibility, etc. Luiz Paulo Fávero, Patrícia Belfiore, and Rafael de Freitas Souza.
250 ## - EDITION STATEMENT
Edition statement First edition.
264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE
Place of production, publication, distribution, manufacture London, United Kingdom ;
-- San Diego, California :
Name of producer, publisher, distributor, manufacturer Academic Press, an imprint of Elsevier,
Date of production, publication, distribution, manufacture, or copyright notice 2023.
300 ## - PHYSICAL DESCRIPTION
Extent xii, 648 pages :
Other physical details illustrations (black and white, and colour) ;
Dimensions 28 cm.
336 ## - CONTENT TYPE
Content type term text
Source rdacontent
337 ## - MEDIA TYPE
Media type term unmediated
Source rdamedia
338 ## - CARRIER TYPE
Carrier type term volume
Source rdacarrier
504 ## - BIBLIOGRAPHY, ETC. NOTE
Bibliography, etc. note Includes bibliographic references and index.
505 0# - FORMATTED CONTENTS NOTE
Formatted contents note I. Introduction -- Overview of data science, analytics, and machine learning -- Introduction to R-based language -- II. Applied statistics and data visualization -- Types of variables, measurement scales, and accuracy scales -- Univariate descriptive statistics -- Bivariate descriptive statistics -- Hypotheses tests -- Data visualization and multivariate graphs -- III. Data mining and preparation -- Webscraping and handcrafted robots -- Using application programming interfaces to collect data -- Managing data -- IV. Unsupervised machine learning techniques -- Cluster analysis -- Principal component factor analysis -- Simple and multiple correspondence analysis - V. Supervised machine learning techniques -- Simple and multiple regression models -- Binary and multinomial logistics -- Count-data and zero-inflated -- Generalized linear mixed models -- VI. Improving performance -- Support vector machines -- Classification and regression trees -- Boosting and bagging -- Random forests -- Artificial neural networks -- VII. Spatial analysis -- Working on shapefiles -- Dealing with simple feature objects -- Raster objects -- Exploratory spatial analysis -- VIII. Adding value to your work -- Enhanced and interactive graphs -- Dashboards with R.
520 ## - SUMMARY, ETC.
Summary, etc. Data Science, Analytics and Machine Learning with R explains the principles of data mining and machine learning techniques and accentuates the importance of applied and multivariate modeling. The book emphasizes the fundamentals of each technique, with step-by-step codes and real-world examples with data from areas such as medicine and health, biology, engineering, technology and related sciences. Examples use the most recent R language syntax, with recognized robust, widespread and current packages. Code scripts are exhaustively commented, making it clear to readers what happens in each command. For data collection, readers are instructed how to build their own robots from the very beginning. In addition, an entire chapter focuses on the concept of spatial analysis, allowing readers to build their own maps through geo-referenced data (such as in epidemiologic research) and some basic statistical techniques. Other chapters cover ensemble and uplift modeling and GLMM (Generalized Linear Mixed Models) estimations, both linear and nonlinear. --
Assigning source Provided by publisher.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Business
General subdivision Data processing.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Machine learning.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element R (Computer program language).
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Belfiore, Patrícia Prado,
Relator term author.
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name De Freitas Souza, Rafael,
Relator term author
906 ## - LOCAL DATA ELEMENT F, LDF (RLIN)
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942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme Dewey Decimal Classification
Koha item type Books
Edition 23
Classification part 658.05631
Item part F278d
Call number prefix GRD
Call number suffix 2023
Suppress in OPAC No
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Home library Current library Shelving location Date acquired Total Checkouts Full call number Barcode Date last seen Copy number Price effective from Koha item type
    Dewey Decimal Classification     Main Library Main Library Graduate School Library 09/02/2025   GRD 658.05631 F278d 2023 030255 09/02/2025 1-2 09/02/2025 Books
    Dewey Decimal Classification     Main Library Main Library Graduate School Library 09/02/2025   GRD 658.05631 F278d 2023 030256 09/02/2025 2-2 09/02/2025 Books