It is funny, what you are usually supposed to be replacing /automating with ML is the nasty 100 line conditional statement that forms some bit of "business logi

It is funny, what you are usually supposed to be replacing /automating with ML is the nasty 100 line conditional statement that forms some bit of "business logic" that nobody really understands. This thing usually being the time pressured fever dream of some dev that left the company years ago. Now it is replaced by something that is even more incomprehensible. If it is done well then at least you get performance guarantees and the ability to retrain. If it is done badly, then you don't know what the features are, which model belongs with which dataset, how to regenerate training sets, where the original training set went, how to set the hyperparameters to get reasonable training performance, etc, etc.