1. Machine learning models where coefficients cannot readily be derived. Should we insist that the model object is shared in these cases? Does this create issues if the object includes the training data (can be tricky to fully remove)?
1. Machine learning models where coefficients cannot readily be derived. Should we insist that the model object is shared in these cases? Does this create issues if the object includes the training data (can be tricky to fully remove)?