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From "Kai Jiang (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (SPARK-13489) GSoC 2016 project ideas for MLlib
Date Thu, 25 Feb 2016 12:46:18 GMT

    [ https://issues.apache.org/jira/browse/SPARK-13489?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15167158#comment-15167158
] 

Kai Jiang commented on SPARK-13489:
-----------------------------------

Here is a [post|http://apache-spark-developers-list.1001551.n3.nabble.com/GSoC-Interested-in-GSoC-2016-ideas-td16224.html]
I published on dev mailing list. (paste it here)
{quote}
Hi All Spark Devs,

I am Kai Jiang, a master student majoring in Computer Science. Machine Learning and Distributed

System are my interests. Due to that, I've been contributing to Spark codebase since last
year. My
Pull Requests are related to MLlib, PySpark and SQL.(https://github.com/apache/spark/pulls/vectorijk)

Last time, I was impressed by the MechCoder's project mentored by mengxr. This year, I look
forward
to having a chance to do something interesting and want to extend my future contribution with
Spark
into a GSoC project. Thus, I was wondering if there are some specific ideas, issues or suggestions
regarding MLlib (mainly), SQL or others could be gathered into a project. After looking into
the MLlib 2.0
Roadmap, I found there are many issues I am interested in (i.e Python/SparkR API for ML, PMML
export,
etc.). If community has other ideas, I am very willing to work on some issues before GSoC.
{quote}

I will put here a link of my very rough draft proposal later.

> GSoC 2016 project ideas for MLlib
> ---------------------------------
>
>                 Key: SPARK-13489
>                 URL: https://issues.apache.org/jira/browse/SPARK-13489
>             Project: Spark
>          Issue Type: Brainstorming
>          Components: ML
>            Reporter: Xiangrui Meng
>            Assignee: Xiangrui Meng
>            Priority: Minor
>
> I want to use this JIRA to collect some GSoC project ideas for MLlib. Ideally, the student
should have contributed to Spark. And the content of the project could be divided into small
functional pieces so that it won't get stalled if the mentor is temporarily unavailable.



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