automl is pretty horrible if you're doing anything that is complicated, even at Google-scale compute power SotA DNNs are hand crafted, not auto-found. Feature e

automl is pretty horrible if you're doing anything that is complicated, even at Google-scale compute power SotA DNNs are hand crafted, not auto-found. Feature engineering is also quite important for a lot of data types and that has too large of a phase space to probe with automl. At the same time if your problems are mostly solved by logistic regression/random forest/etc with simple features (ie you have well defined categories and/or states or your task is well solved in literature) then ML is not your value proposition, it's more data/business analytics (and autoML should enable you to provide your value faster).