> For the complete documentation index, see [llms.txt](https://awsnotes.dendron.so/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://awsnotes.dendron.so/machine-learning/amazon-rekognition/common/tutorials.md).

# Tutorials

{% hint style="info" %}
This page was generated from content adapted from the [AWS Developer Guide](https://github.com/awsdocs/amazon-rekognition-developer-guide.git)
{% endhint %}

## Using Amazon Rekognition and Lambda to tag assets in an Amazon S3 bucket

* **Note**\
  The services you use in this tutorial are part of the AWS Free Tier. When you are done with the tutorial, we recommend terminating any resources you created during the tutorial so that you are not charged.
* **Note**\
  Make sure you assign your bucket name to the **bucketName** variable.
* **Note**\
  Notice the use of the **maven-shade-plugin** in the project’s POM file. This plugin is responsible for creating a JAR that contains the required dependencies. If you attempt to package up the project without this plugin, the required dependences are not included in the JAR file and you will encounter a **ClassNotFoundException**.

## Creating an Amazon Rekognition Lambda function

* **Note**\
  This tutorial uses the AWS SDK for Java 1.x. For a tutorial using Rekognition and the AWS SDK for Java version 2, see the [AWS Documentation SDK examples GitHub repository](https://github.com/awsdocs/aws-doc-sdk-examples/tree/master/javav2/usecases/video_analyzer_application).
* **Note**\
  Use the same AWS Region throughout the tutorial.


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## 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, and the optional `goal` query parameter:

```
GET https://awsnotes.dendron.so/machine-learning/amazon-rekognition/common/tutorials.md?ask=<question>&goal=<endgoal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal.

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.