Outside of linear regression (if you consider that a ML method) it seems like we do not check the residuals after building our ML model. Is there a reason for this? Even if we don't make assumptions like normality, couldn't the residuals offer some information if there is some discernible pattern? Or do most ML methods do a good job at removing any kind of pattern.