The Shogun Machine Learning Toolbox

EuroPython talk by: Heiko Strathmann, herrstrathmann.de
 
 
Strathmann presented the Shogun toolbox. Shogun is a Machine Learning toolbox which implement most of the common supervised and unsupervised algorithms. Shogun is implemented in C++ and interacts with Python as well as with Java, Ruby, Matlab, Lau, etc. Shogun is meant to run on single machine and no distributed.
 
Shogun is an open source project started on 2004. It has 8 core developers + 20 contributors and it is fairly active. It also has a collebaration with Google summer of code – 29 projects so far, 8 on going.
 
The C++ maybe the most significant advantage of Shogun over SciPy. It is simply faster and enables more efficient memory allocation and run time optimization and well as multi-language support . Therefore enabling training and classifying data based on larger number of samples and higher dimension.
 
The binding \ interfaces to other languages is done using – http://www.swig.org

Building, bug tracing and deployment is done using – http://buildbot.net/.

 
Summarizing – Specially when going larger Shogun seems like a good alternative to SciPy (competition makes both products better). Shogun site offers some tutorials include notebooks and demos.
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