Get Started


There are multiple ways to get mlpack up and running. Python bindings can be installed using pip or conda, or built from source (see “Build from source” tutorials). Julia bindings can be installed via Julia’s Pkg package manager.

For C++, if mlpack is not available via your preferred OS package manager, or if you need to build your own version (e.g. to apply optimizations, use a different set of BLAS/LAPACK, or build a different configuration), please refer to the “Build from source” tutorials. For Windows, prebuilt binaries will help you get started without the need of building mlpack. These packages include both the C++ mlpack library as well as the CLI tools.

Once you get mlpack running, check out the documentation or the examples repository, which contains simple example usages of mlpack.

Here is a summary of the currently available distribution options you can use depending on your needs:


Get via pip or conda

pip install mlpack
conda install -c conda-forge mlpack


  • From your workspace dropdown, select Create -> Library. Then specify PyPI and use “mlpack” as the package name.


Get via Pkg

import Pkg;

Ubuntu, Debian, Fedora, Red Hat

Install using a package manager

Build from source


Download prebuilt binaries

Install using a package manager

Build from source


Install using homebrew

brew install mlpack

Build from source