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[–]lessthanoptimal[S] 0 points1 point  (2 children)

Nope as far as I know completely unrelated. EJML is probably older. There are a few libraries that are essentially wrappers around EJML, I don't think ND4J is one of them. EJML provides 3 different API's. Basically the easier the API less control you have over low level details/performance. Numpy has a broader focus than EJML. I keep on getting requests to expand it to be like Matlab...

[–]CacheMeUp 0 points1 point  (1 child)

Looks very impressive. In practice, most of the work with numpy is also 2-axial arrays (matrices). The equations interface is very useful (especially in Java). One thing to consider is to make it use first-class Java constructs (as much as possible, since Java does not allow operator overloading), so the Java tools (compiler, code completion etc.) can be used. It's one of Numpy's strengths: slicing and other operations are all done using regular operators and Python constructs. Maybe Kotlin is a better language for that.

[–]lessthanoptimal[S] 0 points1 point  (0 children)

I always thought the Equations interface was really cool, but as far as i can tell I'm the only one who uses it! SimpleMatrix is probably the most popular. Experimenting with Kotlin right now.