How to generate visual reports on data and model performance.
Dashboard helps visually explore and evaluate the data and model performance.
You can generate dashboards in certain notebook environments (see full list below) or using the command-line interface. The dashboards can be displayed directly in the notebook, or exported as a separate HTML file.
To specify which analysis you want to perform, you should select a Tab (for example, a DataDriftTab). You can combine several tabs in a single Dashboard (for example, for Data Drift and Prediction Drift). Each tab contains a combination of metrics, interactive plots, and tables for a chosen Report type.
For a step-by-step introduction, we recommend you to go first through the Getting Started tutorial.

Supported environments

You can generate the dashboards in Jupyter notebooks.
If you want to display the dashboards in Jupyter notebook, make sure you installed the Jupyter nbextension.
You can also use Google Colab, Kaggle Kernel, or Deepnote. Review the related section for some details.
If you use Jupyter Lab, you won't be able to explore the reports inside a Jupyter notebook. However, the report generation in a separate HTML file will work correctly.
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