All Tutorials
Code examples and tutorials.
Last updated
Code examples and tutorials.
Last updated
Check the short Quickstart examples here.
Introductory tutorials that walk you through the basic functionality step by step.
| Title | Guide | Code |
|---|---|---|
Simple examples show different local evaluations (Metrics, Tests and Presets) for tabular data and ML.
| Title | Code example | Contents |
|---|---|---|
For LLM and text metrics, check the LLM evaluation tutorial.
To better understand the Evidently use cases, refer to the detailed tutorials accompanied by the blog posts.
You can find more examples in the Community Examples repository.
For code examples on specific functionality, check the How-To examples:
To see how to integrate Evidently in your prediction pipelines and use it with other tools, refer to the integrations.
| Title | Tutorial |
|---|---|
| Title | Code example | Blog post |
|---|---|---|
LLM Evaluation
Data & ML Monitoring
LLM Tracing
Intro to Reports & Test Suites (OSS)
Self-host ML monitoring Dashboard (OSS)
Evidently Test Presets
Pre-built Test Suites on tabular data:
Data Drift
Data Stability
Data Quality
NoTargetPerformance
Regression
Classification (Multi-class, binary, binary top-K)
Evidently Tests
All individual Tests (50+) that one can use to create a custom Test Suite. Tabular data examples.
How to set test conditions and parameters.
Evidently Metric Presets
All pre-built Reports:
Data Drift
Target Drift
Data Quality
Regression
Classification
Evidently Metrics
All individual metrics (30+) that one can use to create a custom Report.
How to set simple metric parameters.
Evidently LLM Metrics
Evaluations for Text Data and LLMs
How to create LLM judge evaluator
How to run regression testing for LLM products
Understand ML model decay in production (regression example)
Compare two ML models before deployment (classification example)
Evaluate and visualize historical data drift
Monitor NLP models in production
Create ML model cards
Use descriptors to monitor text data