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https://issues.apache.org/jira/browse/SPARK-6192?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14351030#comment-14351030
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David J. Manglano edited comment on SPARK-6192 at 3/6/15 10:23 PM:
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Hello,
I am experienced in Python, have an interest in machine learning, and have some
knowledge of the graph and probability theory involved in machine learning
methods. I am also interested in the use of cluster computing in scientific
data analysis.
I would like to work on this project for GSoC 2015. What skills would be
required, and what would be the next step?
Thanks!
was (Author: manglano):
Hello,
I am experienced in Python, have an interest in machine learning, and have some
knowledge of the graph and probability theory involved. I am also interested in
the use of cluster computing in scientific data analysis.
I would like to work on this project for GSoC 2015. What skills would be
required, and what would be the next step?
Thanks!
> 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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