This feature is in Public Preview.

The Experiments page gives you quick access to MLflow experiments across your organization. You can track machine learning model development by logging to these experiments from Azure Databricks notebooks and jobs.

To access this page, click Experiments Icon Experiments in the sidebar. This icon appears only when you are in the machine learning persona.

Experiments page

You can view, search for, and create experiments. Only experiments that you have access to in your current workspace appear on this page.

  • To display an experiment page, click the name of an experiment in the table.
  • To search for experiments, type text in the Search field and click Search. The experiment list changes to show only those experiments that contain the search text in the Name, Location, Created by, or Notes column.
  • To create a new experiment, use the create experiment drop-down drop-down menu. From the drop-down menu, you can select either an AutoML experiment or a blank (empty) experiment.
    • AutoML experiment. The Configure AutoML experiment page displays. See Databricks AutoML for information about using AutoML.

    • Blank experiment. The Create MLflow Experiment dialog appears. Enter a name and optional artifact location in the dialog. The default artifact location is dbfs:/databricks/mlflow-tracking/<experiment-id>. See Create workspace experiment for more details.

      To log runs to this experiment, call mlflow.set_experiment() with the experiment path. The experiment path appears at the top of the experiment page. See Log runs to a notebook or workspace experiment for details and an example notebook.