Don't put data science notebooks into production

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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