소장자료
| LDR | 02494cam a2200000 a | ||
| 001 | 0100442580▲ | ||
| 005 | 20200102110407▲ | ||
| 007 | ta ▲ | ||
| 008 | 190701s2019 flua 001 0 eng c▲ | ||
| 020 | ▼a9780367357986 (hbk.)▲ | ||
| 020 | ▼z9780429341830 (PDF)▲ | ||
| 035 | ▼a(KERIS)REF000019046763▲ | ||
| 040 | ▼aLBSOR/DLC▼beng▼cDLC▼dDLC▼d221016▲ | ||
| 082 | 0 | 4 | ▼a005.362▼223▲ |
| 090 | ▼a005.362▼bI68i▲ | ||
| 100 | 1 | ▼aIrizarry, Rafael A.▲ | |
| 245 | 1 | 0 | ▼aIntroduction to data science :▼bdata analysis and prediction algorithms with R /▼cRafael A. Irizarry.▲ |
| 260 | ▼aBoca Raton :▼bCRC Press,▼c2019.▲ | ||
| 300 | ▼axxx, 713 p. :▼bill. ;▼c26 cm.▲ | ||
| 500 | ▼aIncludes index.▲ | ||
| 505 | 0 | ▼aInstalling R and RStudio -- Getting started with R and RStudio -- R Basics -- Programming basics -- The tidyverse -- Importing data -- Introduction to data visualization -- ggplot2 -- Visualizing data distributions -- Data visualization in practice -- Data visualization principles -- Robust summaries -- Introduction to statistics with R -- Probability -- Random variables -- Statistical inference -- Statistical models -- Regression -- Linear models -- Association is not causation -- Introduction to data wrangling -- Reshaping data -- Joining tables -- Web scraping -- String processing -- Parsing dates and times -- Text mining -- Introduction to machine learning -- Smoothing -- Cross validation -- The caret package -- Examples of algorithms -- Machine learning in practice -- Large datasets -- Clustering -- Introduction to productivty tools -- Accessing the terminal and installing Git -- Organizing with Unix -- Git and GitHub -- Reproducible projects with RStudio and R markdown.▲ | |
| 520 | ▼a"The book begins by going over the basics of R and the tidyverse. You learn R throughout the book, but in the first part we go over the building blocks needed to keep learning during the rest of the book"--Provided by publisher.▲ | ||
| 650 | 0 | ▼aR (Computer program language)▲ | |
| 650 | 0 | ▼aInformation visualization.▲ | |
| 650 | 0 | ▼aData mining.▲ | |
| 650 | 0 | ▼aStatistics▼xData processing.▲ | |
| 650 | 0 | ▼aProbabilities▼xData processing.▲ | |
| 650 | 0 | ▼aComputer algorithms.▲ | |
| 650 | 0 | ▼aQuantitative research.▲ |
Introduction to data science :data analysis and prediction algorithms with R
자료유형
국외단행본
서명/책임사항
Introduction to data science : data analysis and prediction algorithms with R / Rafael A. Irizarry.
발행사항
Boca Raton : CRC Press , 2019.
형태사항
xxx, 713 p. : ill. ; 26 cm.
일반주기
Includes index.
내용주기
Installing R and RStudio -- Getting started with R and RStudio -- R Basics -- Programming basics -- The tidyverse -- Importing data -- Introduction to data visualization -- ggplot2 -- Visualizing data distributions -- Data visualization in practice -- Data visualization principles -- Robust summaries -- Introduction to statistics with R -- Probability -- Random variables -- Statistical inference -- Statistical models -- Regression -- Linear models -- Association is not causation -- Introduction to data wrangling -- Reshaping data -- Joining tables -- Web scraping -- String processing -- Parsing dates and times -- Text mining -- Introduction to machine learning -- Smoothing -- Cross validation -- The caret package -- Examples of algorithms -- Machine learning in practice -- Large datasets -- Clustering -- Introduction to productivty tools -- Accessing the terminal and installing Git -- Organizing with Unix -- Git and GitHub -- Reproducible projects with RStudio and R markdown.
요약주기
"The book begins by going over the basics of R and the tidyverse. You learn R throughout the book, but in the first part we go over the building blocks needed to keep learning during the rest of the book"--Provided by publisher.
주제
ISBN
9780367357986 (hbk.)
청구기호
005.362 I68i
소장정보
예도서예약
서서가에없는책 신고
보보존서고신청
캠캠퍼스대출
우우선정리신청
배자료배달신청
문문자발송
출청구기호출력
학소장학술지 원문서비스
| 등록번호 | 청구기호 | 소장처 | 도서상태 | 반납예정일 | 서비스 |
|---|
북토크
자유롭게 책을 읽고
느낀점을 적어주세요
글쓰기
느낀점을 적어주세요
청구기호 브라우징
관련 인기대출 도서