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From "Udit Arora (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (STATISTICS-7) Stream-based Java statistical processing
Date Mon, 01 Apr 2019 19:30:00 GMT

    [ https://issues.apache.org/jira/browse/STATISTICS-7?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16807103#comment-16807103
] 

Udit Arora commented on STATISTICS-7:
-------------------------------------

Sir Gilles
I may not be the best but I have very deep knowledge of linear algebra or matrix algebra as
you said. I have studied this topic in detail, and am familiar with all of the mathematics
part. It actually is one of my favorite fields of mathematics. It has been one of our courses
in 1st semester. From determinant to eigenvectors, SVD I have knowledge of mathematics part
completely. There surely must be more than that, but I am familiar with this topic to a good
level. If I am of any in this regard let me know.

> Stream-based Java statistical processing
> ----------------------------------------
>
>                 Key: STATISTICS-7
>                 URL: https://issues.apache.org/jira/browse/STATISTICS-7
>             Project: Apache Commons Statistics
>          Issue Type: New Feature
>            Reporter: Eric Barnhill
>            Priority: Major
>              Labels: GSoC2019, gsoc2019, statistics, streams
>
> The new component aims to be a library of commons statistics functions synchronized
with the latest developments in the Java language, in particular Java's functional programming
syntax.
> The library will make commonly used statistical functions available to an end user through
a simple grammar comparable to commons-math-statistics or scikit-learn, while under the hood
will implement Java's mapping, streaming, and other producer and consumer functions to ensure
the statistical methods run optimally in new Java implementations.
> Developers working on the project will have the opportunity to demonstrate Java programming,
functional programming, algorithm design, and data science skills and receive authorship on a
commons project that is likely to be widely used.
> The ideal contributor will also be able to help with important architectural decision
making. The old source of these libraries, commons-math, grew too large, hierarchically complex
and interdependent for the commons mission. The developers on this project need to make architectural
choices that will enable the statiscal code to be lightweight and reusable, with a minimum
of outside dependencies while avoiding redundancy.



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