Hi @rahuja,
You can create dashboards in Databricks using MLflow data. To achieve this, you can leverage the mlflow.search_runs API to pull aggregate metrics from your MLflow runs and display them in a custom dashboard1. Regularly reviewing these metrics can provide insight into your progress and productivity. For example, you can track improvements in goal metrics like revenue or accuracy over time, across multiple runs and experiments. Additionally, you can use MLflow data to create Databricks tables for further analysis.
If you need more details or assistance, feel free to ask! ๐