Examples

Sample notebooks and tutorials

Sample notebooks
Simple examples on toy datasets to show what Evidently can do out of the box. Colab examples contain pre-rendered reports.
Title
Jupyter notebook
Colab notebook
Contents
Evidently Test Presets
​link​
​link​
All pre-built Test Suites:
Data Drift
Data Stability
Data Quality
NoTargetPerformance
Regression
Classification (Multi-class, binary, binary top-K)
Evidently Tests
​link​
​link​
All individual tests (50+) that one can use to create a custom Test Suite.
How to set simple test parameters.
Evidently Metric Presets
​link​
​link​
All pre-built Reports:
Data Drift
Target Drift
Data Quality
Regression
Classification
Evidently Metrics
​link​
​link​
All individual metrics (30+) that one can use to create a custom Report.
How to set simple metric parameters.
Tutorials
To better understand potential use cases for Evidently (such as model evaluation and monitoring), refer to the detailed tutorials accompanied by the blog posts.
Title
Jupyter notebook
Colab notebook
Blog post
Data source
Monitor production model decay
​link​
​link​
​How to break a model in 20 days. A tutorial on production model analytics.​
Bike sharing UCI: link​
Compare two models before deployment
​link​
​link​
​What Is Your Model Hiding? A Tutorial on Evaluating ML Models.​
HR Employee Attrition: link​
Evaluate and visualize historical drift
​link​
​link​
​How to detect, evaluate and visualize historical drifts in the data.​
Bike sharing UCI: link​
Integrations
To see how to integrate Evidently in your prediction pipelines and use it with other tools, refer to the integrations.
Integrations

Title	Jupyter notebook	Colab notebook	Contents
Evidently Test Presets	link	link	All pre-built Test Suites: Data Drift Data Stability Data Quality NoTargetPerformance Regression Classification (Multi-class, binary, binary top-K)
Evidently Tests	link	link	All individual tests (50+) that one can use to create a custom Test Suite. How to set simple test parameters.
Evidently Metric Presets	link	link	All pre-built Reports: Data Drift Target Drift Data Quality Regression Classification
Evidently Metrics	link	link	All individual metrics (30+) that one can use to create a custom Report. How to set simple metric parameters.

Title	Jupyter notebook	Colab notebook	Blog post	Data source
Monitor production model decay	link	link	How to break a model in 20 days. A tutorial on production model analytics.	Bike sharing UCI: link
Compare two models before deployment	link	link	What Is Your Model Hiding? A Tutorial on Evaluating ML Models.	HR Employee Attrition: link
Evaluate and visualize historical drift	link	link	How to detect, evaluate and visualize historical drifts in the data.	Bike sharing UCI: link

Text Overview

Integrations

Last modified 1mo ago