[wpietri]

I agree that one shouldn't apply ML in a commercial context without understanding it. But I think that's true about almost anything. I can't think of a technology I use for which I don't have a corresponding "novices did it all wrong" story.

But here we're talking about a series of intro videos and the appropriate pedagogical approach. It really could be that ML has more subtle failure modes than programming, although I'm suspicious; I remember a lot of my novice C issues where the program did happen to appear to work, at least for short periods, even though my code was terrible. But if it is, I think the trick there isn't to prescribe a heavier dose of theory, it's to get people to experience problems like you describe in a way where they can quickly detect and learn from them.