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https://issues.apache.org/jira/browse/SPARK-16365?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16031083#comment-16031083
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Nick Pentreath commented on SPARK-16365:
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Databricks has also indicated some work on this in a [blog
post|https://databricks.com/blog/2017/03/28/demand-webinar-faq-apache-spark-mllib-2-x-productionize-machine-learning-models.html]
and Q&A to a webinar
[here|https://forums.databricks.com/questions/11246/dbml-local-looks-very-much-like-mleap-open-source.html#answer-11247].
Perhaps they have some insights to share.
> 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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