مكتبة جامعة عجلون الوطنية

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

By: Material type: TextPublisher: Boca Raton : CRC Press, [2020]Description: xxx, 713 pages : color illustrations (some color) ; 26 cmContent type:
  • text
Media type:
  • unmediated
Carrier type:
  • volume
ISBN:
  • 9780367357986
Subject(s): Additional physical formats: Online version:: Introduction to data science.DDC classification:
  • 005.362 23
LOC classification:
  • QA276.45.R3 I75 2020
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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Books مكتبة جامعة عجلون الوطنية QA276.45.R3.I75 2020 (Browse shelf(Opens below)) Available e4006
Books مكتبة جامعة عجلون الوطنية QA276.45.R3.I75 2020 (Browse shelf(Opens below)) Available e4005

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.

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