# About ML packages

> An ML package is a folder with all the code and metadata needed to train and serve a machine learning model. An ML Package can have multiple versions and is in some way analogous to a [package](https://docs.uipath.com/orchestrator/automation-cloud/latest/user-guide/about-packages) in Orchestrator. Each version can have an associated change log. It is recommended that users acting as Data Scientists handle packages.

An ML package is a folder with all the code and metadata needed to train and serve a machine learning model. An ML Package can have multiple versions and is in some way analogous to a [package](https://docs.uipath.com/orchestrator/automation-cloud/latest/user-guide/about-packages) in Orchestrator. Each version can have an associated change log. It is recommended that users acting as Data Scientists handle packages.

In order to be used within your workflows in Studio, you first have to deploy them as skills in your tenant.

The **ML Packages** page, accessible from the **ML Packages** menu after selecting a project, enables you to view all the available versions of a package, along with their statuses, change logs, and pipelines. Here you can upload new packages or new versions for existing ones, delete undeployed packages, view available information about them, or manage their pipelines.

![Screenshot including the ML Packages menu in UiPath AI Center.](https://dev-assets.cms.uipath.com/assets/images/ai-center/ai-center-screenshot-including-the-ml-packages-menu-in-uipath-ai-center-450479-14c22a29-f8560517.webp)

Select a package from the list to navigate to its corresponding **ML Package Details** page.