Fantastic!

Thanks,
Ambrose


On Mon, Aug 25, 2014 at 2:15 AM, Mikera <[email protected]>
wrote:

> Hi All,
>
> Prasant and Aleksandr have been working all summer making Clojure even
> better for data science / numerical computing. On behalf of myself and my
> co-mentor Alex Ott I want to offer congratulations to them both for
> successfully completing their Google Summer of Code projects!
>
> Thanks to Prasant, we now have full, idiomatic, linear algebra support for
> Clojure. The implementation (part of vectorz-clj) is pure JVM code - i.e.
> no need for native dependencies. In terms of performance, we are already
> competitive with many Java matrix implementations and with some further
> optimisation could easily be one of the fastest linear algebra libaries on
> the JVM. To see the results of Prasant's work, check out core.matrix,
> vectorz-clj and vectorz.
>
> https://github.com/mikera/core.matrix
> https://github.com/mikera/vectorz
> https://github.com/mikera/vectorz-clj
>
> Thanks to Aleksandr, we have completed the Incanter / core.matrix
> implementation work which will make it possible to use core.matrix
> implementations seamlessly within Incanter 2.0. You can use regular Clojure
> vectors (nested persistent vectors of numbers), vectorz-clj (pure JVM,
> double precision), Clatrix (native BLAS support) or any combination of
> these. There is also new, improved "Dataset" support which makes it
> possible to create custom dataset types by implementing some new dataset
> protocols. To see the results of Aleksandr's work, check out Incanter,
> Clatrix and core.matrix
>
> https://github.com/incanter/incanter
> https://github.com/tel/clatrix/commits/master
> https://github.com/mikera/core.matrix
>
> Taken together, these projects represent a significant step towards making
> Clojure a leading language for data science and analytics.
>
> Well done Prasant and Aleksandr!
>
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