ML assumes that the data-generating process can be approximated based on economic theory, but traditional statistical techniques do not make this assumption.

Unlike in ML, the role of computer algorithms in traditional econometric and statistical techniques generally goes beyond estimating the parameters and checking for statistical significance.

Analyses of goodness of fit and residual diagnostics are both relevant for ML but not for the traditional techniques, as they are mainly concerned with the accuracy of forecasts.