description
Sample notebooks and tutorials

Sample notebooks

These simple examples show what Evidently can do out of the box. Head to Colab examples to see the 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 the use cases, refer to the detailed tutorials accompanied by the blog posts.

Title	Code example	Blog post
Understand ML model decay in production (regression example)	Jupyter notebook	How to break a model in 20 days. A tutorial on production model analytics.
Compare two ML models before deployment (classification example)	Jupyter notebook	What Is Your Model Hiding? A Tutorial on Evaluating ML Models.
Evaluate and visualize historical data drift	Jupyter notebook	How to detect, evaluate and visualize historical drifts in the data.
Monitor NLP models in production	Colab	Monitoring NLP models in production: a tutorial on detecting drift in text data
Create ML model cards	Jupyter notebook	A simple way to create ML Model Cards in Python
Use descriptors to monitor text data	Jupyter notebook	Monitoring unstructured data for LLM and NLP with text descriptors

To see how to integrate Evidently in your prediction pipelines and use it with other tools, refer to the integrations.

{% content-ref url="../integrations/evidently-integrations.md" %} integrations/evidently-integrations.md {% endcontent-ref %}