[hervature]

I like to say "the dollars are in the data". Tools like these do open up ML to a wider audience but it does nothing for them to understand that nothing beats proper record keeping and data collection. Furthermore, it handicaps you in certain ways. For example, how are missing values handled?

[syntaxing]

Totally agree, getting actionable and confident results from ML is a really tough thing to do. Imputing data, feature processing, metric choices, and etc is almost an art form (though new AutoML libraries have made this much easier).