Issue 2023-W26 Highlights

Releasing an Word document table into the land of markdown, a practical overview of sharing your machine learning model with others, and taking local control of checking the builds of your package across computing architectures. Episode Links This week's curator: Colin Fay - [@_ColinFay]](https://twitter.com/_ColinFay) (Twitter) Convert a Word table to Markdown How Can Someone Else Use My Model? How to debug your package in a {rhub} fedora container before sending to CRAN? Entire issue available at rweekly.org/2023-W26 Supplement Resources {datapasta} RStudio addins and R functions that make copy-pasting vectors and tables to text painless https://milesmcbain.github.io/datapasta Matt Kaye's series "The missing semester of your DS education" https://matthewrkaye.com/serie....s.html#the-missing-s Put R in production: Tools and guides to put R models in production https://putrinprod.com {checkhelper} A package to help you deal with devtools::check outputs https://thinkr-open.github.io/checkhelper Remote Explorer Visual Studio Code extension https://marketplace.visualstud....io.com/items?itemNam {crew}: A distributed worker launcher framework for asynchronous and distributed computing https://wlandau.github.io/crew Data4Good Explores Visualizing Freshwater Resources on a Global Scale https://appsilon.com/visualizi....ng-fresh-water-resou Supporting the show Use the contact page at https://rweekly.fireside.fm/contact to send us your feedback R-Weekly Highlights on the Podcastindex.org - You can send a boost into the show directly in the Podcast Index. First, top-up with Alby, and then head over to the R-Weekly Highlights podcast entry on the index. A new way to think about value: https://value4value.info Get in touch with us on social media Eric Nantz: @theRcast (Twitter) and @rpodcast@podcastindex.social (Mastodon) Mike Thomas: @mike_ketchbrook (Twitter) and @mike_thomas@fosstodon.org (Mastodon)