I am putting together some material on common mistakes that occur in data science.

The problem, is people often don't talk about the mistakes that everyone has made.

Are there any good resources of real-world examples of these mistakes, and their consequences?

Note: Specific examples are good, but I'm looking for a repository of many mistakes.

  • $\begingroup$ A close vote for "opinion based"?? A data science erorr is as well defined as any code related question. $\endgroup$
    – GooJ
    Sep 24, 2022 at 8:32
  • $\begingroup$ The Help Center is very clear on the type of "constructive subjective questions" that are allowed. This question meets at least three: (i) if they invite sharing experiences over opinions (ii) insist that opinion be backed up with facts and references and (iii) are more than just mindless social fun. For these reasons, I believe that this is an acceptable and valid question [...] $\endgroup$
    – pod
    Oct 10, 2022 at 5:49
  • $\begingroup$ [...] still, I find it a bit odd that you are requesting resources for a resource that you yourself want to create. Perhaps it would help if you could show what work you have done to answer your own question, and what type of examples might you find useful. $\endgroup$
    – pod
    Oct 10, 2022 at 5:52
  • $\begingroup$ @ope Good points, thank you - I'll get around to editing the question. $\endgroup$
    – GooJ
    Oct 13, 2022 at 12:16


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