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https://issues.apache.org/jira/browse/SPARK-6192?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14379777#comment-14379777
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min cheng commented on SPARK-6192:
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Hello,all, I am a candidate for Professional master of University of Chinese
Academy of Sciences. I major in cloud computing and Machine Learning. Now, I am
preparing for the application for this project of GSoC 2015.
I have a good foundation of Python and have a good understanding of all the
common algorithms of machine Learning, I also have done some application upon
Machine Learning, I even participated the ALIDATA DISCOVERY competition last
year. Besides, I have 3-year experience in using Hadoop platforms, I proficient
in MapReduce computing framework. Furthermore, I have been learning Spark for
half a year.
Do you think it is suitable for me to apply this project of GSoC 2015? waiting
for your advice.Thank !
> 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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