MLflow can be used to track (hyper)parameters and metrics when training machine learning models. It stores the trained model as an artifact for every experiment. These models then can be directly deployed as SageMaker endpoints.
Is it possible to do it the other way around, too, i.e. to register models trained in SageMaker into MLflow?