Introduction
mlpack is an intuitive, fast, and flexible C++ machine learning library with bindings to other languages. It is meant to be a machine learning analog to LAPACK, and aims to implement a wide array of machine learning methods and function as a "swiss army knife" for machine learning researchers. The mlpack website can be found at https://mlpack.org.
How To Use This Documentation
This documentation is API documentation similar to Javadoc. It isn't necessarily a tutorial, but it does provide detailed documentation on every namespace, method, and class.
Each mlpack namespace generally refers to one machine learning method, so browsing the list of namespaces provides some insight as to the breadth of the methods contained in the library.
To generate this documentation in your own local copy of mlpack, you can use the 'doc' CMake target, which is available if CMake has found Doxygen, from the build directory:
Tutorials
A few short tutorials on how to use mlpack are given below.
- Building mlpack From Source
- Building mlpack From Source on Windows
- Matrices in mlpack
- Writing an mlpack binding
- mlpack Timers
- Simple Sample mlpack Programs
- Sample C++ ML App for Windows
- Cross-Validation
- Hyper-Parameter Tuning
- mlpack version information
Final Remarks
For the list of contributors to mlpack, see https://www.mlpack.org/community.html. This library would not be possible without everyone's hard work and contributions!