You need to be intimately aware of your data input, the models you’re proposing, and initialisations. Practically, this means iteratively visualising your data

You need to be intimately aware of your data input, the models you’re proposing, and initialisations. Practically, this means iteratively visualising your data and making informed judgements to even make your model run without humans thinking much about the structure of the data and model. The ML promise is that there are robust models that you can feed nearly unlimited amounts of data to get better predictions. Probabilistic modeling is better for people who have a fixed dataset they can visualise and fit an elegant model that incorporates lots of prior information about the problem of interest.