What's the normal way machine-learning algorithms are integrated into normal programs?
- by Benjamin Pollack
I'm currently taking a machine learning course for fun, and the course heavily focuses on Matlab/Octave to write the code. One thing mentioned in the course is that, while Matlab/Octave are great for prototyping, they're very rarely used for production algorithms. Instead, those algorithms are typically rewritten in C++/Python/etc., using appropriate libraries, before reaching customers.
Fair enough; I get that. But here's my question: is that done for cultural reasons, for technical reasons, or because there is really no language that provides Matlab/Octave-like fluidity, but in a compiled form that can be linked from C/C++/$MainstreamLanguage? The game industry uses Lua for game logic because it's easy to embed, and vastly superior for expressing things like AI. Likewise, there are Prolog variants for rules-heavy applications, Scheme variants for compilers, and so on.
If there's a matrix equivalent language, what is it? If there isn't, why is this field different?
