  The Stoner-Wohlfarth is the most used model of magnetic hysteresis, but its
computation is time-consuming. We use machine learning to approximate piecewise
this model by easy-to-compute analytic functions. Our parametrization is
suitable for fast quantitative evaluations and fitting experimental data, which
we exemplify.
