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# Deployment
Once a modeling pipeline is ready for deployment, it is easy to deploy mlpack
applications to a wide variety of settings due to its simple header-only nature.
See also the [examples repository](https://github.com/mlpack/examples/),
which contains a number of fully-working deployable example applications.
The pages below provide guidance for how to deploy mlpack to a variety of
relatively simple environments.
* [***Compile an mlpack program***](compile.md): compile a standalone C++ program
that uses mlpack.
* [***Cross-compile to a Raspberry Pi***](../embedded/crosscompile_armv7.md):
cross-compile an mlpack C++ application to an embedded or low-resource
device.
- See also the
[cross-compilation setup page](../embedded/supported_boards.md).
* [***Deploying mlpack on Windows***](deploy_windows.md): build a Windows
application that uses mlpack.
* [***Deploying mlpack to a Docker container***](deploy_docker.md): package an
mlpack application inside of a lightweight Docker container for local usage
or deployment in a cloud environment.
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