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Posted to issues@spark.apache.org by "Xiangrui Meng (JIRA)" <ji...@apache.org> on 2015/05/27 09:02:17 UTC
[jira] [Commented] (SPARK-6192) Enhance MLlib's Python API (GSoC
2015)
[ https://issues.apache.org/jira/browse/SPARK-6192?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14560528#comment-14560528 ]
Xiangrui Meng commented on SPARK-6192:
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[~bu_min] Sorry for my late response! As I mentioned above, it would be great if you can start with some small features or helping review others' PRs. We need to know each other before we can plan a GSoC project. This is a good place to start: https://cwiki.apache.org/confluence/display/SPARK/Contributing+to+Spark
> 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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