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https://issues.apache.org/jira/browse/SPARK-6192?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14365918#comment-14365918
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Xiangrui Meng commented on SPARK-6192:
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[~MechCoder] Please be a little (but not too) specific in the proposal. For
example, you should mention Python in the title of the proposal, which sets the
theme of the project. Scala/Java will be definitely involved, but the goal is
to have a better coverage of MLlib's Python API. This also helps reviewers
understand the scope the proposal and rate it.
You should also mention in the proposal that if the features are implemented by
others, we will create new tasks within the theme of the project. So it is good
for both MLlib and GSoC.
> Enhance MLlib's Python API (GSoC 2015)
> --------------------------------------
>
> Key: SPARK-6192
> URL: https://issues.apache.org/jira/browse/SPARK-6192
> Project: Spark
> Issue Type: Umbrella
> Components: ML, MLlib, PySpark
> Reporter: Xiangrui Meng
> Assignee: Manoj Kumar
> Labels: gsoc, gsoc2015, mentor
>
> This is an umbrella JIRA for [~MechCoder]'s GSoC 2015 project. The main theme
> is to enhance MLlib's Python API, to make it on par with the Scala/Java API.
> The main tasks are:
> 1. For all models in MLlib, provide save/load method. This also
> includes save/load in Scala.
> 2. Python API for evaluation metrics.
> 3. Python API for streaming ML algorithms.
> 4. Python API for distributed linear algebra.
> 5. Simplify MLLibPythonAPI using DataFrames. Currently, we use
> customized serialization, making MLLibPythonAPI hard to maintain. It
> would be nice to use the DataFrames for serialization.
> I'll link the JIRAs for each of the tasks.
> Note that this doesn't mean all these JIRAs are pre-assigned to [~MechCoder].
> The TODO list will be dynamic based on the backlog.
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