Scientific Machine Learning

Scientific Machine Learning implements the science-of-counting to analytically process any time-series and produce a
complete set of thermodynamic measurements that define the state of the system. The scientific measurements are
first illustrated with a time-series of closing-prices on a stock. Exact scientific measurements from Scientific Machine
Learning (SML) are then directed to create time-series decision services, without model or bias, which we call a Decision
Machine. A Decision Machine service is defined for a large class of Open allocation problems and applied to optimal sales
for a consumer product good.