mlpack

mlpack is a machine learning software library for C++, built on top of the Armadillo library. mlpack has an emphasis on scalability, speed, and ease-of-use. Its aim is to make machine learning possible for novice users by means of a simple, consistent API, while simultaneously exploiting C++ language features to provide maximum performance and maximum flexibility for expert users.[3] Its intended target users are scientists and engineers.

mlpack
Initial releaseFebruary 1, 2008 (2008-02-01)[1]
Stable release
3.3.2 / June 18, 2020 (2020-06-18)[2]
Repository
Written inC++, Python, Julia, Go
Operating systemCross-platform
Available inEnglish
TypeSoftware library Machine learning
LicenseOpen source (BSD)
Websitemlpack.org 

It is open-source software distributed under the BSD license, making it useful for developing both open source and proprietary software. Releases 1.0.11 and before were released under the LGPL license. The project is supported by the Georgia Institute of Technology and contributions from around the world.

Miscellaneous features

Template classes for GRU, LSTM structures are available, thus the library also supports Recurrent Neural Networks.

There are bindings to R, Go, Julia[4], and Python. Its binding system is extensible to other languages.

Supported algorithms

Currently mlpack supports the following algorithms and models:

mlpack uses the ensmallen mathematical optimization library for training many of the above models.

gollark: Oh, and if you look at versions where it's "pull lever to divert trolley onto different people" versus "push person off bridge to stop trolley", people tend to be less willing to sacrifice one to save five in the second case, because they're more involved and/or it's less abstract somehow.
gollark: There might be studies on *that*, actually, you might be able to do it without particularly horrible ethical problems.
gollark: You don't know that. We can't really test this. Even people who support utilitarian philosophy abstractly might not want to pull the lever in a real visceral trolley problem.
gollark: Almost certainly mostly environment, yes.
gollark: It's easy to say that if you are just vaguely considering that, running it through the relatively unhurried processes of philosophizing™, that sort of thing. But probably less so if it's actually being turned over to emotion and such, because broadly speaking people reaaaallly don't want to die.

See also

References
  1. "Initial checkin of the regression package to be released · mlpack/mlpack". February 8, 2008. Retrieved May 24, 2020.
  2. "Releases - mlpack/mlpack". Retrieved 15 July 2020 – via GitHub.
  3. Ryan Curtin; et al. (2013). "mlpack: A Scalable C++ Machine Learning Library". Journal of Machine Learning Research. 14 (Mar): 801–805. arXiv:1210.6293. Bibcode:2012arXiv1210.6293C.
  4. https://github.com/mlpack/mlpack.jl
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