Learning
137 items from iamericfletcher/awesome-r-learning-resources ★664
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Coolors coolors.co
The super fast color schemes generator! Create the perfect palette or get inspired by thousands of beautiful color schemes. Features include color picker, pick palette from photo, create a collage, make your own gradient palette, create a gradient, contrast checker, etc.
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R Bloggers r-bloggers.com
R-Bloggers.com was created by Tal Galili and is a blog aggregator of content contributed by bloggers who write about R (in English). The site helps R bloggers and users to connect and follow the R blogosphere.
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R for Data Science by Garrett Grolemund & Hadley Wickham r4ds.had.co.nz
This book will teach you how to do data science with R. You will learn how to get your data into R, get it into the most useful structure, transform it, visualize it and model it. Exercise Solutions Authors: Garrett Grolemund and Hadley Wickham.
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Text Mining with R tidytextmining.com
This book serves as an introduction of text mining using the tidytext package and other tidy tools in R. Authors: Julia Silge and David Robinson.
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The R Graph Gallery r-graph-gallery.com
A collection of charts made with the R programming language. Author: Yan Holtz.
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Not so Standard Deviations nssdeviations.com
A data science podcast where Roger Peng and Hilary Parker talk about the latest in data science and data analysis in academia and industry.
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From Data to Viz data-to-viz.com
From Data to Viz leads you to the most appropriate graph for your data. Author: Yan Holtz.
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The R-Podcast r-podcast.org
Practical advice on how to take advantage of R to accomplish innovative and robust data analyses. Hosted by Eric Nantz.
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R Programming for Data Science by Roger D. Peng (2019) leanpub.com
This book brings the fundamentals of R programming to you, using the same material developed as part of the industry-leading Johns Hopkins Data Science Specialization. Author: Roger Peng.
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htmlwidgets htmlwidgets.org
Showcase and gallery of the various interactive web visualizations you can build using R.
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Efficient R Programming by Colin Gillespie & Robin Lovelace (2017) csgillespie.github.io
Efficient R Programming is about increasing the amount of work you can do with R in a given amount of time. It’s about both computational and programmer efficiency. Authors: Colin Gillespie, Robin Lovelace.
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The R Inferno by Patrick Burns (2011) burns-stat.com
A book about trouble spots, oddities, traps, and glitches in R. Author: Patrick Burns.
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Ben Stenhaug youtube.com
Topics include saving and reading data, map functions in purrr, t-tests, item response theory, and the basics of R and the tidyverse.
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Cédric Scherer youtube.com
A collection of talks and seminars about R-related topics such as ggplot2 or Shiny, and data visualization in general.
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StatQuest with Josh Starmer youtube.com
The Statistics and Machine Learning in R playlist deals with principal component analysis, random forest, regression, ROC and AUC, and ridge, lasso and elastic-net.
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RichardOnData youtube.com
The R playlist includes videos on manipulating data with dplyr, visualizing data with ggplot2 and ggThemeAssist, data types and structures, important base r functions, handling datetimes with lubridate, conquering factors with forcats, manipulating text with stringr.
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Simplilearn youtube.com
The R Programming for Beginners playlist includes videos on data science, charting, data visualization, algorithms, business analytics, regression, random forest, SVM, clustering, time series, modeling, and analytical techniques.
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IDG TECHtalk youtube.com
Do More with R playlist includes tutorials on shiny, data.table, getting API data, using Git and Github with R, writing your own packages, run Python in R code, RStudio addins and keyboard shortcuts, dashboards and flexdashboards.
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David Jablonski youtube.com
The UC Berkeley R Bootcamp playlists include videos on R basics, handling data, performing calculations, programming, graphics, workflows, and statistics.
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Statistics Globe youtube.com
A collection of short but detailed tutorials on how to work through common problems you will face while using R. Topics include data formatting, reordering data, strings, and ggplot2.
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Data Analysis and Visualization Using R youtube.com
Topics for the online course Data Analysis and Visualization Using R.
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David Robinson youtube.com
Topics include graphing for EDA, data manipulation, animated mapping, visualization, text mining, time series, forecasting, regression, bootstrapping, package development, network graphs, ANOVA, JSON, simulation, survival analysis, and tidymetrics. Click here for detailed…
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Data Science with Tom youtube.com
Topics include time series, analyzing word relationships with ggraph and tidytext, and tidymodels.
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Julia Silge youtube.com
Topics include predictive text modeling, impute missing data, tidymodels, sentiment analysis, multinomial classification, principal component analysis, data preprocessing and resampling, and multinomial classification.
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TidyX youtube.com
TidyX is a screen cast where the hosts select code from the TidyTuesday project and go through their code line-by-line, explaining what they did and how the functions they used work. They also break down the visualizations they create and talk about how to apply similar…
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Richard Webster youtube.com
Topics include the paste function, the apply family of functions, while and for loops, conditional statements, visualization, removing NAs, and combining data.
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MarinStatsLectures youtube.com
Topics include descriptive statistics, ANOVA, bootstrapping, linear regression, bivariate analysis, and probability distributions.
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