Finally, we introduce the Jammy Key for Machine Learning (JKML) that interfaces with the QML and SchNetPack packages. This interface facilitates the application of machine learning techniques from the KRR and NN families. We outline the potential integration of ML into the configurational sampling procedure and deliberate on their applicability with respect to the training data set size. We believe that incorporating machine learning techniques holds substantial promise to reduce the computational expenses associated with future investigations of molecular clusters.