Machine Learning Toolbox Overview

This summary provides a comprehensive overview of popular machine learning toolkits including LIBLINEAR, VW, Torch, Theano, Shogun, and Stan. It covers basic information, licenses, supported platforms, parallel computing capabilities, interfaces, Gitreport statistics, and collaborations with esteemed institutions. Explore the features, licenses, platforms, parallel computing options, interfaces, and partnerships of these machine learning frameworks.

• Machine learning
• Toolbox
• LIBLINEAR
• Torch
• Shogun

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Uploaded on Feb 24, 2025 | 0 Views

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Presentation Transcript

1. Summary so far

2. Basic info LIBLINEAR: Linear classification & regression VW: Online linear learning, feature manipulations and reductions Torch: Deep learning, flexible scripting and interpreter, packages Theano: Deep learning, flexible python library Shogun: Kernel methods, toolkit with many interfaces and hooks Stan: Sampling, statistical modelling

3. Licenses & Language Liblinear VW Torch Theano Shogun Stan BSD BSD BSD BSD GPLv3 BSD/GPL C/C++ C++ Lua Python C++ C++

4. Platforms Liblinear VW Torch Theano Shogun Stan Unix Unix Unix Unix Unix Unix Windows Windows Windows Windows Mac iOS Mac Mac Mac Android

5. Parallel? Liblinear VW Torch Theano Shogun Stan Multicore Multicore(threads) Multicore(blas) Yes(?) No Cluster Cluster Cluster (MPI/Spark) GPU GPU

6. Interfaces Liblinear VW Torch Theano Shogun Stan Cmd Cmd Cmd Cmd Cmd Cmd Matlab Library Library Matlab Octave Octave C# Java Daemon Python Python Python Python Ruby Perl Weka R R R Lisp Scilab

7. Gitreport Liblinear VW Torch Theano Shogun Stan 5 49 19 84 77 29 Contributors 134 2736 390 15393 13489 8096 Commits 11 1533 467 756 450 231 Star 8 380 79 273 301 72 Fork 2007 (LIBSVM 2000) 2009 2012 2008 2006 2011 Since

8. $$ Liblinear VW Torch Theano Shogun Stan NTU Microsoft/Yahoo Facebook/NEC/ NYU/Idiap U Montreal MPI Columbia