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.
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