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 <ul> <li>This week&#39;s curator: Colin Fay - [@_ColinFay]](<a href="https://twitter.com/_ColinFay" rel="nofollow">https://twitter.com/_ColinFay</a>) (Twitter)</li> <li><a href="https://www.rostrum.blog/2023/06/21/wordup-tables/" rel="nofollow">Convert a Word table to Markdown</a></li> <li><a href="https://matthewrkaye.com/posts/series/doing-data-science/2023-06-20-how-can-others-use-my-model/how-can-others-use-my-model.html" rel="nofollow">How Can Someone Else Use My Model?</a></li> <li><a href="https://statnmap.com/2023-06-20-how-to-debug-your-package-in-a-rhub-fedora-container-before-sending-to-cran/" rel="nofollow">How to debug your package in a {rhub} fedora container before sending to CRAN?</a></li> <li>Entire issue available at <a href="https://rweekly.org/2023-W26.html" rel="nofollow">rweekly.org/2023-W26</a></li> </ul> Supplement Resources <ul> <li><code>{datapasta}</code> RStudio addins and R functions that make copy-pasting vectors and tables to text painless <a href="https://milesmcbain.github.io/datapasta" rel="nofollow">https://milesmcbain.github.io/datapasta</a></li> <li>Matt Kaye&#39;s series &quot;The missing semester of your DS education&quot; <a href="https://matthewrkaye.com/series.html#the-missing-semester-of-your-ds-education" rel="nofollow">https://matthewrkaye.com/series.html#the-missing-semester-of-your-ds-education</a></li> <li>Put R in production: Tools and guides to put R models in production <a href="https://putrinprod.com" rel="nofollow">https://putrinprod.com</a></li> <li><code>{checkhelper}</code> A package to help you deal with <code>devtools::check</code> outputs <a href="https://thinkr-open.github.io/checkhelper" rel="nofollow">https://thinkr-open.github.io/checkhelper</a></li> <li>Remote Explorer Visual Studio Code extension <a href="https://marketplace.visualstudio.com/items?itemName=ms-vscode.remote-explorer" rel="nofollow">https://marketplace.visualstudio.com/items?itemName=ms-vscode.remote-explorer</a> </li> <li><code>{crew}</code>: A distributed worker launcher framework for asynchronous and distributed computing <a href="https://wlandau.github.io/crew" rel="nofollow">https://wlandau.github.io/crew</a></li> <li>Data4Good Explores Visualizing Freshwater Resources on a Global Scale <a href="https://appsilon.com/visualizing-fresh-water-resources-data" rel="nofollow">https://appsilon.com/visualizing-fresh-water-resources-data</a></li> </ul> Supporting the show <ul> <li>Use the contact page at <a href="https://rweekly.fireside.fm/contact" rel="nofollow">https://rweekly.fireside.fm/contact</a> to send us your feedback</li> <li><a href="https://podcastindex.org/podcast/1062040" rel="nofollow">R-Weekly Highlights on the Podcastindex.org</a> - You can send a boost into the show directly in the Podcast Index. First, top-up with <a href="https://getalby.com/" rel="nofollow">Alby</a>, and then head over to the R-Weekly Highlights podcast entry on the index.</li> <li>A new way to think about value: <a href="https://value4value.info" rel="nofollow">https://value4value.info</a> </li> <li>Get in touch with us on social media <ul> <li>Eric Nantz: <a href="https://twitter.com/theRcast" rel="nofollow">@theRcast</a> (Twitter) and <a href="https://podcastindex.social/@rpodcast" rel="nofollow">@rpodcast@podcastindex.social</a> (Mastodon)</li> <li>Mike Thomas: <a href="https://twitter.com/mike_ketchbrook" rel="nofollow">@mike_ketchbrook</a> (Twitter) and <a href="https://fosstodon.org/@mike_thomas" rel="nofollow">@mike_thomas@fosstodon.org</a> (Mastodon)</li> </ul></li> </ul>

Eric Nantz

The R Weekly podcast offers a quick description of the latest highlighted stories and other stories from the latest R Weekly issue, as curated by the R Weekly team and R community.

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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.