Introduction to data science : data analysis and prediction algorithms with R / Rafael A. Irizarry.

By: Irizarry, Rafael A [author.]Material type: TextTextSeries: CHAPMAN & HALL/CRC DATA SCIENCE SERIESPublisher: Boca Raton : CRC Press, Taylor & Francis Group, [2020]Description: 713pContent type: text Media type: computer Carrier type: online resourceISBN: 9780429341830Subject(s): R (Computer program language) | Information visualization | Data mining | Statistics -- Data processing | Probabilities -- Data processing | Computer algorithms | Quantitative research | E-BOOKBANK.SEECSTEXTBOOKAdditional physical formats: Print version:: Introduction to data scienceDDC classification: 005.362 LOC classification: QA276.45.R3Online resources: Click here to access online
Contents:
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.
Summary: "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.
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Item type Current location Home library Call number Status Date due Barcode Item holds
Book Book Central Library (CL)
Central Library (CL)
280 SCB (Browse shelf) Available SCB-1537
Book Book Central Library (CL)
Central Library (CL)
005.362 IRI (Browse shelf) Available CL-1537
Total holds: 0

Includes bibliographical references and index.

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.

"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.

Description based on online resource; title from PDF title page (Site, viewed 04/05/2021).

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