Here you can find simple examples on toy datasets to quickly explore what Evidently can do right out of the box. Each shows how to create a default Evidently dashboard, a JSON profile and an HTML report.
Report | Jupyter notebook | Colab notebook | Data source |
---|---|---|---|
Getting Started Tutorial | link | link | California housing sklearn.datasets |
Evidently Metrics | link | link | Adult data set openml |
Evidently Metric Presets | link | link | Adult data set openml, California housing sklearn.datasets, Breast cancer sklearn.datasets, Iris plants sklearn.datasets |
Evidently Tests | link | link | Adult data set openml, California housing sklearn.datasets, Breast cancer sklearn.datasets, Iris plants sklearn.datasets |
Evidently Test Presets | link | link | Adult data set openml, California housing sklearn.datasets, Breast cancer sklearn.datasets, Iris plants sklearn.datasets |
To learn how to adjust evidently as you need, refer to the how-to questions.
To better understand potential use cases (such as model evaluation and monitoring), refer to the detailed tutorials accompanied by the blog posts.
To see how to integrate Evidently in your prediction pipelines and use it with other tools, refer to the integrations.