Don't put data science notebooks into production
fetched at November 18, 2020

We've come across many clients who are interested in taking the computational notebooks developed by their data scientists, and putting them directly into the codebase of production applications. My colleague David Johnston points out that while data science ideas do need to move out of notebooks and into production, trying to deploy that notebooks as a code artifact breaks a multitude of good software practices. Predictably, that results in a number of observed pain points. This behavior is a symptom of a deeper problem: a lack of collaboration between data scientists and software developers.

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