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, 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 a standalone C++ program that uses mlpack.
- Cross-compile to a Raspberry Pi:
cross-compile an mlpack C++ application to an embedded or low-resource
device.
- See also the cross-compilation setup page.
-
Deploying mlpack on Windows: build a Windows application that uses mlpack.
- Deploying mlpack to a Docker container: package an mlpack application inside of a lightweight Docker container for local usage or deployment in a cloud environment.