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https://issues.apache.org/jira/browse/SPARK-16365?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15375928#comment-15375928
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RJ Nowling edited comment on SPARK-16365 at 7/13/16 10:40 PM:
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I'm really looking forward to this feature. Spark is great where model training 
is expensive and involves large data sets but I want to be able to deploy those 
models as part of mobile or other applications without a dependency on Spark. 
It would be especially nice if there were implementations not only for the JVM 
but Python, Go, and other languages. 

[~MechCoder], applying models often requires less computation than training 
them. So use Spark to train then have a local, non distributed library for 
embedding models in other applications is how I interpret the feature.


was (Author: rnowling):
I'm really looking forward to this feature. Spark is great where model training 
is expensive and involves large data sets but I want to be able to deploy those 
models as per of mobile or other applications without a dependency on Spark. It 
would be especially nice if there were implementations only for the JVM but 
Python, Go, and other languages. 

[~MechCoder], applying models often requires less computation than training 
them. So use Spark to train then have a local, non distributed library for 
embedding in other applications is how I interpret the feature.

> Ideas for moving "mllib-local" forward
> --------------------------------------
>
>                 Key: SPARK-16365
>                 URL: https://issues.apache.org/jira/browse/SPARK-16365
>             Project: Spark
>          Issue Type: Brainstorming
>          Components: ML
>            Reporter: Nick Pentreath
>
> Since SPARK-13944 is all done, we should all think about what the "next 
> steps" might be for {{mllib-local}}. E.g., it could be "improve Spark's 
> linear algebra", or "investigate how we will implement local models/pipelines 
> in Spark", etc.
> This ticket is for comments, ideas, brainstormings and PoCs. The separation 
> of linalg into a standalone project turned out to be significantly more 
> complex than originally expected. So I vote we devote sufficient discussion 
> and time to planning out the next move :)



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