Modern data science with R Ed 2 (Record no. 240611)

MARC details
000 -LEADER
fixed length control field 01778nam a22002657a 4500
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20251030092025.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 251030b |||||||| |||| 00| 0 eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781032941677
040 ## - CATALOGING SOURCE
Transcribing agency AL
041 ## - LANGUAGE CODE
Language code of text/sound track or separate title eng
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 006.312
Item number BAUM
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name Benjamin S Baumer and others
100 ## - MAIN ENTRY--PERSONAL NAME
9 (RLIN) 243172
245 ## - TITLE STATEMENT
Title Modern data science with R Ed 2
250 ## - EDITION STATEMENT
Edition statement 2
260 ## - PUBLICATION, DISTRIBUTION, ETC.
Place of publication, distribution, etc. New York
Name of publisher, distributor, etc. CRC Press
Date of publication, distribution, etc. 2021
300 ## - PHYSICAL DESCRIPTION
Extent xvii,631p.
Other physical details HB
Dimensions 25x17.5
365 ## - TRADE PRICE
Source of price type code Computer Science Engineering Artificial Intelligence and Machine Learning
Price type code 4224
Price amount ₹2796.00
Currency code ₹
Unit of pricing ₹3495.00
Price note 20%
Price effective from 23-10-2025
520 ## - SUMMARY, ETC.
Summary, etc. Modern Data Science with R is a comprehensive data science textbook for undergraduates that incorporates statistical and computational thinking to solve real-world problems with data. Rather than focus exclusively on case studies or programming syntax, this book illustrates how statistical programming in the state-of-the-art R/RStudio computing environment can be leveraged to extract meaningful information from a variety of data in the service of addressing compelling statistical questions. Contemporary data science requires a tight integration of knowledge from statistics, computer science, mathematics, and a domain of application. This book will help readers with some background in statistics and modest prior experience with coding develop and practice the appropriate skills to tackle complex data science projects. The book features a number of exercises and has a flexible organization conducive to teaching a variety of semester courses.
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Visualization
9 (RLIN) 243173
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Statistics and Modeling
9 (RLIN) 243174
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Big Data
9 (RLIN) 243175
700 ## - ADDED ENTRY--PERSONAL NAME
Personal name Kaplan, Daniel T
9 (RLIN) 243176
700 ## - ADDED ENTRY--PERSONAL NAME
Personal name Horton, Nicholas J
9 (RLIN) 243177
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 Home library Current library Date acquired Source of acquisition Cost, normal purchase price Total Checkouts Full call number Barcode Date last seen Cost, replacement price Price effective from Koha item type
    Dewey Decimal Classification     Computer Science and Engineering (Artificial Intelligence & Machine Learning) St Aloysius Engineering Library St Aloysius Engineering Library 10/23/2025 Biblios Book Point, Surathkal-575014 2796.00   006.312 BAUM SE000132 10/30/2025 3495.00 10/23/2025 Book