A data scientist set up a machine learning pipeline to automatically log a data visualization with each run. They now want to view the visualizations in Databricks.
Which of the following locations in Databricks will show these data visualizations?
A data scientist set up a machine learning pipeline to automatically log a data visualization with each run. They now want to view the visualizations in Databricks.
Which of the following locations in Databricks will show these data visualizations?
When a data visualization is logged in an MLflow run, it is stored as an artifact. These artifacts can be viewed in the Artifacts section of the corresponding MLflow Run page in Databricks. This allows data scientists to easily access and review the visualizations generated during the run.
The correct answer is D. The Artifacts section of the MLflow Run page. When a data visualization is logged in an MLflow run, it is stored as an artifact of that run. These artifacts can be viewed in the Artifacts section of the corresponding MLflow Run page in Databricks. This allows data scientists to easily access and review the visualizations generated during the run. The MLflow Experiment page provides a high-level overview of all the runs in an experiment, but to view the details of a specific run, including any logged artifacts like data visualizations, you would need to navigate to the specific Run page.
MLflow stores artifacts such as data visualizations in the Artifacts section of the MLflow Run page, allowing users to view them directly within Databricks.