Yeah and it might be. We're targeting the big data folks with this framework frankly.
Anything that does static typing might be overkill for just running matrix math.
I created nd4j with the intent of having the same primitives and programming model accessible to me for production environments and also affording me the same privileges of optimizing things in c with nice clean abstractions.
The JVM and the developers who use it are mainly people with salaries soliving a very specific class of problems not people publishing papers. The one exception to this I've seen is the NLP community. I'd argue it's just a different audience who needs the things the jvm has, eg: static typing, integrations with libraries, etc.
For large codebases you really can't beat jvm tooling..if you just need a click repl and throwaway code? It might be a bit much if you don't already know it.
Anything that does static typing might be overkill for just running matrix math.
I created nd4j with the intent of having the same primitives and programming model accessible to me for production environments and also affording me the same privileges of optimizing things in c with nice clean abstractions.
scala MIGHT be easier which is why we created nd4s: https://github.com/deeplearning4j/nd4s
The JVM and the developers who use it are mainly people with salaries soliving a very specific class of problems not people publishing papers. The one exception to this I've seen is the NLP community. I'd argue it's just a different audience who needs the things the jvm has, eg: static typing, integrations with libraries, etc.
For large codebases you really can't beat jvm tooling..if you just need a click repl and throwaway code? It might be a bit much if you don't already know it.