In this session the lecturer discussed current challenges of using machine learning in the context of environmental monitoring. More specifically, the suitability of different cross-validation strategies to assess the prediction performance, including novel developments like the “nearest neighbor distance matching” method, were discussed. The lecturer enabled the attendees to further learn how suitable cross-validation strategies can be used to improve prediction models by applying them during hyperparameter tuning and variable selection. Finally, she thaugh them about the “area of applicability” of spatial prediction models – to limit predictions to the area where the model was enabled to learn about relationships. In the first part of the session, she guided the attendees through the motivation and conceptual ideas of these methods. In the second session how to apply these methods in practice. The newly suggested methods are implemented in the R package CAST which we will use together with the R package caret, but the attendees also learned how to use the methods with mlr3.