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Deep R Programming

integration_instructionsResearch softwarekeyboard_double_arrow_right Software 29 Dec 2022Publisher:Zenodo
Authors: Gagolewski, Marek;
Code repository: https://github.com/gagolews/deepr/tree/v0.1.12

doi: 10.5281/zenodo.7490465 , 10.5281/zenodo.7811712 , 10.5281/zenodo.8088889 , 10.5281/zenodo.7869924 , 10.5281/zenodo.7947808 , 10.5281/zenodo.13379827

Deep R Programming

Abstract

Deep R Programming is a comprehensive course on one of the most popular languages in data science (statistical computing, graphics, machine learning, data wrangling and analytics). It introduces the base language in-depth and is aimed at ambitious students, practitioners, and researchers who would like to become independent users of this powerful environment. This textbook is a non-profit project. Its online and PDF versions are freely available at https://deepr.gagolewski.com/.

Please cite this book as below.

Keywords

S, graphics, R, programming, data frames, data cleansing, machine learning, vectors, tensors, statistics, matrices, data science, text processing, data wrangling

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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