# Module 3: ML monitoring for unstructured data

This module covers evaluating and monitoring the production performance for models that use unstructured data, including LLM-based systems.

We will cover:

* Why monitoring unstructured data is difficult;
* How to measure text data quality;
* What are text descriptors and how to use them;
* How to deal with embeddings;
* How to deal with multimodal data.

This module includes both a **theoretical part and code practice**. At the end of this module, you will understand the possible approaches to monitoring ML models that work with texts and other unstructured data.


---

# 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://learn.evidentlyai.com/ml-observability-course/module-3-ml-monitoring-for-unstructured-data.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.