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As a practical example, brain.js is a very limited neural network library. You can only provide a dataset and train on that dataset. You can't implement any var
by Houshalter 12y ago
As a practical example, brain.js is a very limited neural network library. You can only provide a dataset and train on that dataset. You can't implement any variations like dropout, stochastic gradient descent, momentum, etc.
Whereas a good neural network library like Torch lets you work at a much lower level of abstraction. You can put together individual layers, and it gives you the internal code for doing forward and backward passes, and chaining them together.
- kiyoto 12y agoThat's exactly what I am talking about. Your anti-example is a case of library-level abstraction. Now, if you are saying that JavaScript doesn't lend itself to writing extensible machine learning routines whereas Lua does, it's a different story.