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R for the Rest of Us Podcast Episode #22: Alex Gold

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Manage episode 455078347 series 3564735
Content provided by David Keyes. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by David Keyes or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ppacc.player.fm/legal.

In this episode, I chat with Alex Gold, who leads solution engineering and support teams at Posit. We talk about his new book ‘DevOps for Data Science’, and explore why DevOps principles are crucial for data scientists, even if you aren't working in hardcore production environments. Alex shares insights on how to think about putting your data science projects into "production"—whether it's a report for colleagues or a full-scale deployment. We discuss practical tips like using {renv} to manage package versions and ensure reproducibility, and Alex gives a live demo on setting it up in an R project. Tune in for key takeaways on making your data science work more robust, shareable, and ready for production.

Important resources mentioned:

Connect with Alex on:

Subscribe to our newsletter: https://rfortherestofus.com/newsletter

  continue reading

27 episodes

Artwork
iconShare
 
Manage episode 455078347 series 3564735
Content provided by David Keyes. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by David Keyes or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ppacc.player.fm/legal.

In this episode, I chat with Alex Gold, who leads solution engineering and support teams at Posit. We talk about his new book ‘DevOps for Data Science’, and explore why DevOps principles are crucial for data scientists, even if you aren't working in hardcore production environments. Alex shares insights on how to think about putting your data science projects into "production"—whether it's a report for colleagues or a full-scale deployment. We discuss practical tips like using {renv} to manage package versions and ensure reproducibility, and Alex gives a live demo on setting it up in an R project. Tune in for key takeaways on making your data science work more robust, shareable, and ready for production.

Important resources mentioned:

Connect with Alex on:

Subscribe to our newsletter: https://rfortherestofus.com/newsletter

  continue reading

27 episodes

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