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https://issues.apache.org/jira/browse/COMDEV-118?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14351721#comment-14351721
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Lee moon soo edited comment on COMDEV-118 at 3/7/15 6:06 PM:
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Hi Zezhong ZHANG,
Really appreciate for the interest.
I think data that we want to use is any interesting data, which is licensed to
use in this kind of Purpose.
About "interactive machine learning", i think the subject is wide open.
>From integration with existing machine learning software and giving them
>ability to analysis,
(Recently published integration with PredictionIO
http://docs.prediction.io/datacollection/analytics-zeppelin/),
Some utility library or visualization that helps machine learning can be used
in interactive notebook in Zeppelin,
to any new great idea.
Thanks.
was (Author: moon):
Hi Zezhong ZHANG,
Really appreciate for the interest.
I think data that we want to use is any interesting data, which is licensed to
use in this kind of Purpose.
About "interactive machine learning", i think the subject is wide open.
>From integration with existing machine learning software and giving them
>ability to analysis,
(Recently published integration with PredictionIO
http://docs.prediction.io/datacollection/analytics-zeppelin/),
Some utility library or visualization that helps machine learning can be used
in interactive notebook in Zeppelin,
to any new great idea.
Welcome!
> Zeppelin GSoC Project: create a ML\Deeplearning tutorial notebook
> -----------------------------------------------------------------
>
> Key: COMDEV-118
> URL: https://issues.apache.org/jira/browse/COMDEV-118
> Project: Community Development
> Issue Type: Task
> Reporter: Alexander Bezzubov
> Labels: deeplearning, gsoc2015, machine_learning, scala, spark
>
> Zeppelin as generic notebook interpreter system for cluster computing is
> capable of connecting different distributed systems. The main focus right now
> is Apache Spark which itself have extensive machine learning facilities.
> There are other systems such as H2O, PredictIO, Parameterserver or Singa
> implementing advanced techniques based on neural networks, commonly referred
> as Deeplearning.
> The goal of this Google Summer of Code project is to develop a tutorial
> Notebook with a sample data and extend Zeppelin server to be able to show
> advantages of interactive machine learning.
> Stunents are welcome to reach out Zeppelin community via its developers
> mailing list to discuss the details, see
> http://zeppelin.incubator.apache.org/community.html
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