[Radim]

Could be. Using Jupyter for ML development or even prototyping (as opposed to presentations / demonstration / teaching like the OP — that's where Jupyter really shines) is a red flag.

I see a similar pattern with Pandas: some people use Pandas not because it's the right tool for the job (Pandas has many strengths), but because they're scared of writing comprehension loops and basic data structures. To avoid the CS-y stuff. But without the CS-y stuff, the result ends up a mess of lambdas, weird reindexing and buggy copy/view semantics.

And then "the next guy", the one who's job it is to clean up and productionalize the maverick's output, ends up having to reinvent and fix the entire solution. Basically doing both jobs.

[bosie]

How do you suggest prototyping without Jupyter? (in case prototyping means researching an approach)