According to the Databricks MLflow documentation, you can specify a custom artifact location when creating a new experiment using the;
artifact_location parameter of the mlflow.create_experiment
This will override the default artifact location (/databricks/mlflow)
However, if you want to change the default artifact location for all experiments, you may need to set an environment variable called
MLFLOW_TRACKING_URI
to point to your desired cloud storage path before running any MLflow code. This will tell MLflow where to store and retrieve artifacts for all experiments.
