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by cbo
5323 days ago
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This article doesn't really describe what the title implies. It states issues and concerns for several languages, names several that have large ML libraries written for them already, and even gives his own approach for how to implement new ML algorithms, but it doesn't actually give real options for "Programming Languages for Machine Learning". I've found that Matlab/Octave is a decent substitute for a "high-level language" to sketch out new approaches with. They're significantly fast, as well as significantly suited to matrix algebra that they can give decent results, even though they have some less-than-beautiful code. Matlab appears to be the language of choice for AI at the University of Toronto. Personally, I think the best option would be to roll with a functional language (or at least, a language with functions as first-class objects), since a lot of ML algorithms can be reduced to recursion on several matrices, often using very similar functions. For example, ANNs frequently have very similar structures and training strategies, but simply use different learning functions. Everything can be done in C/C++ though, and while it'd be harder, ML is an area where the gain in speed and efficiency is so significant that extra development time pays boatloads in terms of ROI. Even basic ML examples often involve dealing with 300x236 dimensional data, so you can imagine how much that data would scale up significantly in production environments. |
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Don't forget machine learning generally involves a lot of experimentation, and this is easier with higher-level languages. Hand-optmization always makes assumptions about specific data structures and details which can be hard to change later.
You can get very close with code-generating high-level languages though. See Theano (http://deeplearning.net/software/theano/), for example. It uses a functional approach to compose the formulas for (c-)ANNs, and has advanced features such as automatic differentiation. Scalable generated GPU code can beat the pants of even the fastest hand-written C loops. Sure, hand-optimized GPU code can perform even faster but in my experience that is usually not worth the trouble.