Refactoring machine learning code - comments as code

I find that in the field of data science and machine learning some coding principles that are standard in traditional software engineering sometimes are lacking. One such principle is to strive to rather specify everything that is possible in code rather than as comments. Why does it make sense to do that? Comments often don’t age well. You write them in the context of the current code, but then over time as the code gets changed and readapted to other use cases, the context changes....

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