Github user srowen commented on the issue:
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@ngopal this one can't be merged as-is and looks like it was abandoned.
Would you like to take this PR, update per reviews? I'd review that. I think
CBOW could be useful in MLlib.
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Github user ngopal commented on the issue:
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When can we anticipate this branch being merged?
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@shubhamchopra are you still working on this?
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Jenkins OK to test.
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Github user shubhamchopra commented on the issue:
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@hhbyyh Thanks for your suggestions. Will try to incorporate these in a day
or so.
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Thanks for your comments/suggestions @MLnick and @sethah . Working on
incorporating these.
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ok to test
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Github user shubhamchopra commented on the issue:
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Code-review comments/suggestions so far have been incorporated. Thanks for
looking into the code. Happy to incorporate more suggestions and feedback.
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Github user shubhamchopra commented on the issue:
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@MLnick I half expected that. No worries. I have incorporated some of your
feedback in the meantime and also added subsampling as well. Thanks for looking
into the code.
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Github user MLnick commented on the issue:
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FYI, realistically there won't be bandwidth to really focus on this until
after Spark 2.2 QA is done at the earliest.
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Github user Krimit commented on the issue:
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Thanks for the detailed response @shubhamchopra.
I'd like to clarify my point about whether this should be implemented in
Spark: Spark MlLib is first and foremost a framework for doing ML on
Github user shubhamchopra commented on the issue:
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@Krimit
_Can you provide some information about the practical differences between
CBOW and skip-grams?_
 proposed two model
architectures for generating word embeddings, Continuous Skip-Gram model and
continuous Bag-of-words model. Spark ML
Github user hhbyyh commented on the issue:
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Thanks for sharing the work. To help make the review easier, I would
recommend:
1. Provide some background info.
Is the new algorithm better than the existing one and in which cases?
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