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https://issues.apache.org/jira/browse/SPARK-6192?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14352546#comment-14352546
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Manoj Kumar edited comment on SPARK-6192 at 3/9/15 4:51 AM:
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[~Manglano] [~leckie-chn] Hi, I am actually not a mentor but a student whom 
this GSoC project is preassigned to by Xiangrui (since I've been working on the 
Spark codebase for about a couple of months right now) . This project idea was 
actually a result of brainstorming across different Pull Requests. I would 
suggest you have a look at different issues which would help you gain 
familiarity with Spark and help to propose a project proposal. Hope that helps.


was (Author: mechcoder):
[~Manglano] [~leckie-chn] Hi, I am actually not a mentor but a student whom 
this GSoC project is preassigned to by Xiangrui (since I've been working on the 
Spark codebase for about a couple of months right now) . This project idea was 
actually a result of brainstorming across different Pull Requests. I would 
suggest you have a look at different issues which would help you gain 
familiarity with the API and help to propose a project proposal. Hope that 
helps.

> 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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