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Introduction to data science :data a...
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Irizarry, Rafael A.,
Introduction to data science :data analysis and prediction algorithms with R /
Record Type:
Language materials, printed : Monograph/item
Title/Author:
Introduction to data science :Rafael A. Irizarry.
Reminder of title:
data analysis and prediction algorithms with R /
Author:
Irizarry, Rafael A.,
Description:
xxx, 713 pages p. ; 26 cm.
Notes:
Includes index.
Subject:
R (Computer program language)
Online resource:
https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&db=nlabk&AN=2160994
Online resource:
https://public.ebookcentral.proquest.com/choice/publicfullrecord.aspx?p=5981987
Online resource:
https://www.taylorfrancis.com/books/e/9780429341830
ISBN:
9780429341830
Introduction to data science :data analysis and prediction algorithms with R /
Irizarry, Rafael A.,
Introduction to data science :
data analysis and prediction algorithms with R /Rafael A. Irizarry. - xxx, 713 pages p. ; 26 cm.
Includes index.
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 -- Organizing with Unix -- Git and GitHub -- Reproducible projects with RStudio and R markdown.
"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"--
Rafael A. Irizarry is professor of data sciences at the Dana-Farber Cancer Institute, professor of biostatistics at Harvard, and a fellow of the American Statistical Association. Dr. Irizarry is an applied statistician and during the last 20 years has worked in diverse areas, including genomics, sound engineering, and public health. He disseminates solutions to data analysis challenges as open source software, tools that are widely downloaded and used. Prof. Irizarry has also developed and taught several data science courses at Harvard as well as popular online courses.
ISBN: 9780429341830
Source: 9780429341830Taylor & Francis
LCCN: 2019025161Subjects--Topical Terms:
210846
R (Computer program language)
Index Terms--Genre/Form:
214472
Electronic books.
LC Class. No.: QA276.45.R3 / I75 2020
Dewey Class. No.: 005.362
Introduction to data science :data analysis and prediction algorithms with R /
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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 -- Organizing with Unix -- Git and GitHub -- Reproducible projects with RStudio and R markdown.
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Rafael A. Irizarry is professor of data sciences at the Dana-Farber Cancer Institute, professor of biostatistics at Harvard, and a fellow of the American Statistical Association. Dr. Irizarry is an applied statistician and during the last 20 years has worked in diverse areas, including genomics, sound engineering, and public health. He disseminates solutions to data analysis challenges as open source software, tools that are widely downloaded and used. Prof. Irizarry has also developed and taught several data science courses at Harvard as well as popular online courses.
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西方語文圖書區(四樓)
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https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&db=nlabk&AN=2160994
https://public.ebookcentral.proquest.com/choice/publicfullrecord.aspx?p=5981987
https://www.taylorfrancis.com/books/e/9780429341830
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