# All Tutorials

{% hint style="info" %}
**You are looking at the old Evidently documentation**: this API is available with versions 0.6.7 or lower. Check the newer version [here](https://docs.evidentlyai.com/introduction).
{% endhint %}

## Quick Start

Check the short Quickstart examples [here](https://github.com/evidentlyai/docs-old/blob/main/get-started/README.MD).

## Get Started Tutorials

Introductory tutorials that walk you through the basic functionality step by step.

| Title                                   | Guide                                                         | Code                                                                                                                                                                       |
| --------------------------------------- | ------------------------------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| LLM Evaluation                          | [Tutorial](/tutorials-and-examples/tutorial-llm.md)           | [Jupyter notebook](https://github.com/evidentlyai/evidently/blob/ad71e132d59ac3a84fce6cf27bd50b12b10d9137/examples/sample_notebooks/llm_evaluation_tutorial.ipynb)         |
| Data & ML Monitoring                    | [Tutorial](/tutorials-and-examples/tutorial-cloud.md)         | [Jupyter notebook](https://github.com/evidentlyai/evidently/blob/ad71e132d59ac3a84fce6cf27bd50b12b10d9137/examples/sample_notebooks/data_and_ml_monitoring_tutorial.ipynb) |
| LLM Tracing                             | [Tutorial](/tutorials-and-examples/tutorial_tracing.md)       | [Jupyter notebook](https://github.com/evidentlyai/evidently/blob/ad71e132d59ac3a84fce6cf27bd50b12b10d9137/examples/sample_notebooks/llm_tracing_tutorial.ipynb)            |
| Intro to Reports & Test Suites (OSS)    | [Tutorial](/tutorials-and-examples/tutorial_reports_tests.md) | [Jupyter notebook](https://github.com/evidentlyai/evidently/blob/ad71e132d59ac3a84fce6cf27bd50b12b10d9137/examples/sample_notebooks/getting_started_tutorial.ipynb)        |
| Self-host ML monitoring Dashboard (OSS) | [Tutorial](/tutorials-and-examples/tutorial-monitoring.md)    | [Jupyter notebook](https://github.com/evidentlyai/evidently/blob/ad71e132d59ac3a84fce6cf27bd50b12b10d9137/examples/sample_notebooks/get_started_monitoring.py)             |

## Example Reports and Tests

Simple examples show different local evaluations (Metrics, Tests and Presets) for tabular data and ML.

| Title                    | Code example                                                                                                                                                                         | Contents                                                                                                                                                                                                                        |
| ------------------------ | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| Evidently Test Presets   | [Jupyter notebook](https://github.com/evidentlyai/evidently/blob/ad71e132d59ac3a84fce6cf27bd50b12b10d9137/examples/sample_notebooks/evidently_test_presets.ipynb)                    | <p>Pre-built Test Suites on tabular data:</p><ul><li>Data Drift</li><li>Data Stability</li><li>Data Quality</li><li>NoTargetPerformance</li><li>Regression</li><li>Classification (Multi-class, binary, binary top-K)</li></ul> |
| Evidently Tests          | <p><a href="https://github.com/evidentlyai/evidently/blob/ad71e132d59ac3a84fce6cf27bd50b12b10d9137/examples/sample_notebooks/evidently_tests.ipynb">Jupyter notebook</a><br></p>     | <ul><li>All individual Tests (50+) that one can use to create a custom Test Suite. Tabular data examples.</li><li>How to set test conditions and parameters.</li></ul>                                                          |
| Evidently Metric Presets | [Jupyter notebook](https://github.com/evidentlyai/evidently/blob/ad71e132d59ac3a84fce6cf27bd50b12b10d9137/examples/sample_notebooks/evidently_metric_presets.ipynb)                  | <p>All pre-built Reports:</p><ul><li>Data Drift</li><li>Target Drift</li><li>Data Quality</li><li>Regression</li><li>Classification</li></ul>                                                                                   |
| Evidently Metrics        | [Jupyter notebook](https://github.com/evidentlyai/evidently/blob/ad71e132d59ac3a84fce6cf27bd50b12b10d9137/examples/sample_notebooks/evidently_metrics.ipynb)                         | <ul><li>All individual metrics (30+) that one can use to create a custom Report.</li><li>How to set simple metric parameters.</li></ul>                                                                                         |
| Evidently LLM Metrics    | [Jupyter notebook](https://github.com/evidentlyai/evidently/blob/ad71e132d59ac3a84fce6cf27bd50b12b10d9137/examples/how_to_questions/how_to_evaluate_llm_with_text_descriptors.ipynb) | <ul><li>Evaluations for Text Data and LLMs</li></ul>                                                                                                                                                                            |

For LLM and text metrics, check the [LLM evaluation tutorial](/tutorials-and-examples/tutorial-llm.md).

## Tutorials - LLM

| Title                                          | Tutorial                                                               |
| ---------------------------------------------- | ---------------------------------------------------------------------- |
| How to create LLM judge evaluator              | [Tutorial](/tutorials-and-examples/cookbook_llm_judge.md)              |
| How to run regression testing for LLM products | [Tutorial](/tutorials-and-examples/cookbook_llm_regression_testing.md) |

## Tutorials - ML

To better understand the Evidently 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](https://github.com/evidentlyai/community-examples/blob/main/tutorials/bicycle_demand_monitoring.ipynb)                                                            | [How to break a model in 20 days. A tutorial on production model analytics.](https://evidentlyai.com/blog/tutorial-1-model-analytics-in-production)       |
| Compare two ML models before deployment (classification example) | [Jupyter notebook](https://github.com/evidentlyai/community-examples/blob/main/tutorials/ibm_hr_attrition_model_validation.ipynb)                                                    | [What Is Your Model Hiding? A Tutorial on Evaluating ML Models.](https://evidentlyai.com/blog/tutorial-2-model-evaluation-hr-attrition)                   |
| Evaluate and visualize historical data drift                     | [Jupyter notebook](https://github.com/evidentlyai/evidently/blob/ad71e132d59ac3a84fce6cf27bd50b12b10d9137/examples/integrations/mlflow_logging/historical_drift_visualization.ipynb) | [How to detect, evaluate and visualize historical drifts in the data.](https://evidentlyai.com/blog/tutorial-3-historical-data-drift)                     |
| Monitor NLP models in production                                 | [Colab](https://colab.research.google.com/drive/15ON-Ub_1QUYkDbdLpyt-XyEx34MD28E1)                                                                                                   | [Monitoring NLP models in production: a tutorial on detecting drift in text data](https://www.evidentlyai.com/blog/tutorial-detecting-drift-in-text-data) |
| Create ML model cards                                            | [Jupyter notebook](https://github.com/evidentlyai/community-examples/tree/main/tutorials/How_to_create_an_ML_model_card.ipynb)                                                       | [A simple way to create ML Model Cards in Python](https://www.evidentlyai.com/blog/ml-model-card-tutorial)                                                |
| Use descriptors to monitor text data                             | [Jupyter notebook](https://github.com/evidentlyai/community-examples/tree/main/tutorials/How_to_add_a_custom_text_descriptor.ipynb)                                                  | [Monitoring unstructured data for LLM and NLP with text descriptors](https://www.evidentlyai.com/blog/unstructured-data-monitoring)                       |

You can find more examples in the [Community Examples](https://github.com/evidentlyai/community-examples) repository.

### How to examples

For code examples on specific functionality, check the How-To examples:

{% content-ref url="<https://github.com/evidentlyai/evidently/tree/ad71e132d59ac3a84fce6cf27bd50b12b10d9137/examples/how_to_questions>" %}
<https://github.com/evidentlyai/evidently/tree/ad71e132d59ac3a84fce6cf27bd50b12b10d9137/examples/how_to_questions>
{% endcontent-ref %}

### Integrations

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

{% content-ref url="/pages/C83MWVyC3hbvfQawVkV5" %}
[Evidently integrations](/integrations/integrations/evidently-integrations.md)
{% endcontent-ref %}


---

# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://docs-old.evidentlyai.com/tutorials-and-examples/examples.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.