Yup. At the cloud event yesterday one individual pointed out correctly that the problem is that when you give someone a tool they think it's the right tool for everything.
He also explained that public cloud is the right tool for everything. 
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I'm a computational modeler in a experimental psych department so I am coming at it from a very specific perspective.
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no firm conclusion to this tweet, but: there's something in here about several different communities of practice, including active coders, data scientist/scripters + learners, teachers, etc.
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I strongly agree with the conclusion that isn't in this tweet ;) I also think a lot of consternation around notebooks in pedagogy is that they're amazing for learning a new package or trick or visualization >>
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<< _when you're already an experienced programmer in the first place_ From what I've observed, just operating successfully in the jupyter environment seems to require pretty high cognitive overhead and comfort with python (or whatever language)
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Just installing it seems to be hard for newbies especially if they've accidentally mixed and matched between conda, pipt, etc.
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I started hating them when I tried to help my mother get Jupyter working on her Windows PC for an online course while I was up visiting. Both of us are extremely experienced coders and I also had experience setting up Jupyter on Linux and it was a total mess.
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If you compare this to (sorry) the extremely positive experience she had installing Octave for her most recent course, it’s clear Jupyter has a problem.
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Yup, people seem to forget that is true even for experts! I basically cry with frustration when it's that time of year when I have to update CUDA and TensorFlow. It *only* takes like a whole day...

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