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Beginning data science in R 4: data analysis, visualization, and modelling for the data scientist / Thomas Mailund.

By: Material type: TextTextPublisher: California : Apress, 2022Distributor: New York, New York : Distributed by Springer Science + Business MediaCopyright date: 2022Description: xxviii, 511 pages : illustrations ; 26 cmContent type:
  • text
Media type:
  • unmediated
Carrier type:
  • volume
ISBN:
  • 9781484281543
  • 9781484281543
  • 9781484281543
  • 9781484281543
Subject(s): DDC classification:
  • 001.42 23
LOC classification:
  • QA276.45.R3 M349 2017
Contents:
Introduction to R programming -- Reproducible analysis -- Data manipulation -- Visualizing data -- Working with large datasets -- Supervised learning -- Unsupervised learning -- More R programming -- Advanced R programming -- Object oriented programming -- Building an R package -- Testing and package checking -- Version control -- Profiling and optimizing.
Action note:
  • Catalography: 20251031 ferrienalusseferrienalusse
Summary: Discover best practices for data analysis and software development in R and start on the path to becoming a fully-fledged data scientist. This book teaches you techniques for both data manipulation and visualization and shows you the best way for developing new software packages for R. -- Provided by publisher.
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Holdings
Item type Current library Call number Copy number Status Barcode
Books-Closed Access Books-Closed Access School of Food Technology, Nutrition and Bioengineering School of Food Technology, Nutrition and Bioengineering 001.42 MAI (Browse shelf(Opens below)) 1 Available 001239823

Includes index.

Introduction to R programming -- Reproducible analysis -- Data manipulation -- Visualizing data -- Working with large datasets -- Supervised learning -- Unsupervised learning -- More R programming -- Advanced R programming -- Object oriented programming -- Building an R package -- Testing and package checking -- Version control -- Profiling and optimizing.

Discover best practices for data analysis and software development in R and start on the path to becoming a fully-fledged data scientist. This book teaches you techniques for both data manipulation and visualization and shows you the best way for developing new software packages for R. -- Provided by publisher.

Catalography: 20251031 ferrienalusseferrienalusse

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