How to Do Exploratory Data Analysis (EDA) in Machine Learning

A glimpse into the day-to-day of maintaining an R package, exploring gender effects in art history data with the power of resampling, and a huge win for accessible SVG plots with R-Markdown.

Episode Links

• This week's curator: Jon Carroll - @carroll_jono (Twitter) & @jonocarroll@fosstodon.org (Mastodon)
• What Does It Mean to Maintain a Package?
• Resampling to understand gender in #TidyTuesday art history data
• Manipulate SVG Plots with JavaScript in R Markdown
• Entire issue available at rweekly.org/2023-W07

Supplement Resources

• Bootstrap resampling and tidy regression models https://www.tidymodels.org/learn/statistics/bootstrap/
• Accessible Data Science Beyond Visual Models: Non-Visual Interactions with R and RStudio Packages (JooYoung Seo from rstudio::global(2021)) https://www.rstudio.com/resources/rstudioglobal-2021/accessible-data-science-beyond-visual-models-non-visual-interactions-with-r-and-rstudio-packages
• Eric's adventures with Shiny modules and SVG interactions https://community.rstudio.com/t/passing-module-namespace-to-embedded-javascript-function/26988

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