11 open source tools to make the most of machine learning

11 open source tools to make the most of machine learning

Venerable Shogun was created in 1999 and written in C++, but can be used with Java, Python, C#, Ruby, R, Lua, Octave, and Matlab. The latest version, 6.0.0, adds native support for Microsoft Windows and the Scala language.

Though popular and wide-ranging, Shogun has competition. Another C++-based machine learning library, Mlpack, has been around only since 2011, but professes to be faster and easier to work with (by way of a more integral API set) than competing libraries.

Project: Shogun
GitHub: https://github.com/shogun-toolbox/shogun


Source: InfoWorld Big Data