So, can you tell us, when Incanter 2.0 will be released?)

On 25 August 2014 11:08, Ambrose Bonnaire-Sergeant <
abonnaireserge...@gmail.com> wrote:

> Fantastic!
>
> Thanks,
> Ambrose
>
>
> On Mon, Aug 25, 2014 at 2:15 AM, Mikera <mike.r.anderson...@gmail.com>
> 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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