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Modern data science with R

Modern data science with R (Loan 1 times)

Material type
단행본
Personal Author
Baumer, Benjamin. Kaplan, Daniel. Horton, Nicholas J.
Title Statement
Modern data science with R / Benjamin S. Baumer, Daniel T. Kaplan, Nicholas J. Horton.
Publication, Distribution, etc
Boca Raton :   CRC Press,Taylor & Francis Group, CRC Press is an imprint of the Taylor & Francis Group, an informa business,   c2017.  
Physical Medium
xxvi, 551 p. : ill. (soem col.). ; 26 cm.
Series Statement
Texts in statistical science
ISBN
9781498724487 (acid-free paper)
Bibliography, Etc. Note
Includes bibliographical references (p. 499-512) and indexes.
Subject Added Entry-Topical Term
Data mining. Big data. Mathematical statistics --Data processing. R (Computer program language).
000 00000cam u2200205 a 4500
001 000046025295
005 20200421124632
008 200420s2017 flua b 001 0 eng
010 ▼a 2016042514
020 ▼a 9781498724487 (acid-free paper)
035 ▼a (KERIS)REF000018184406
040 ▼a DLC ▼b eng ▼c DLC ▼e rda ▼d DLC ▼d 211009
050 0 0 ▼a QA76.9.D343 ▼b B38 2017
082 0 0 ▼a 006.3/12 ▼2 23
084 ▼a 006.312 ▼2 DDCK
090 ▼a 006.312 ▼b B347m
100 1 ▼a Baumer, Benjamin.
245 1 0 ▼a Modern data science with R / ▼c Benjamin S. Baumer, Daniel T. Kaplan, Nicholas J. Horton.
260 ▼a Boca Raton : ▼b CRC Press,Taylor & Francis Group, CRC Press is an imprint of the Taylor & Francis Group, an informa business, ▼c c2017.
300 ▼a xxvi, 551 p. : ▼b ill. (soem col.). ; ▼c 26 cm.
490 1 ▼a Texts in statistical science
504 ▼a Includes bibliographical references (p. 499-512) and indexes.
650 0 ▼a Data mining.
650 0 ▼a Big data.
650 0 ▼a Mathematical statistics ▼x Data processing.
650 0 ▼a R (Computer program language).
700 1 ▼a Kaplan, Daniel.
700 1 ▼a Horton, Nicholas J.
830 0 ▼a Texts in statistical science.
945 ▼a KLPA

Holdings Information

No. Location Call Number Accession No. Availability Due Date Make a Reservation Service
No. 1 Location Main Library/Western Books/ Call Number 006.312 B347m Accession No. 111827730 Availability Available Due Date Make a Reservation Service B M

Contents information

Table of Contents

This site includes additional resources:
http://mdsr-book.github.io/


Introduction to Data Science


Prologue: Why data science?


Data visualization


A grammar for graphics


Data wrangling


Tidy data and iteration


Professional Ethics


Statistics and Modeling


Statistical foundations


Statistical learning and predictive analytics


Unsupervised learning


Simulation


Topics in Data Science


Interactive data graphics


Database querying using SQL


Database administration


Working with spatial data


Text as data


Network science


Epilogue: Towards \big data"


Appendices


Packages used in this book


Introduction to R and RStudio


Algorithmic thinking


Reproducible analysis and workflow


Regression modeling


Setting up a database server

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