Downloading and Installing mlpack
Prebuilt mlpack packages are available for most operating systems;
these packages may not be the latest version,
so if you are encountering issues,
use the official source release.
Source download and build reference
C++ system-wide package installation
Debian/Ubuntu:
sudo apt-get install libmlpack-devRed Hat/Fedora:
sudo dnf install mlpack-develArch Linux:
sudo pacman -S mlpackmacOS (Homebrew):
brew install mlpackmacOS (MacPorts):
sudo port install mlpackWindows (vcpkg):
vcpkg install mlpackWindows MSI installer:
mlpack-4.3.0.msi
Language-specific installation
Python (pip):
pip install mlpackPython (conda):
conda install -c conda-forge mlpackJulia:
import Pkg; Pkg.add("mlpack");R:
install.packages("mlpack")Go:
go get -u -d mlpack.org/v1/mlpack
Ready-to-use cloud images
Command-line program installation
Debian/Ubuntu:
sudo apt-get install mlpack-binRed Hat/Fedora:
sudo dnf install mlpack-binArch Linux:
sudo pacman -S mlpackmacOS (Homebrew):
brew install mlpackmacOS (MacPorts):
sudo port install mlpackWindows (vcpkg):
vcpkg install mlpackWindows MSI installer:
mlpack-4.3.0.msi
Quickstart: Using mlpack
Once mlpack is installed, you can go through the quickstart tutorials:
You can also look at the
examples repository for fully
working mlpack data science pipelines and applications.
Further documentation
Once mlpack is installed and working, the reference documentation links
below can be helpful for building mlpack applications:
