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From Aseem Bansal <asmbans...@gmail.com>
Subject Re: [ML] MLeap: Deploy Spark ML Pipelines w/o SparkContext
Date Fri, 03 Feb 2017 12:00:41 GMT
Is computational time for predictions on the order of few milliseconds (<
10 ms) like the old mllib library?

On Thu, Feb 2, 2017 at 10:12 PM, Hollin Wilkins <hollin@combust.ml> wrote:

> Hey everyone,
>
>
> Some of you may have seen Mikhail and I talk at Spark/Hadoop Summits about
> MLeap and how you can use it to build production services from your
> Spark-trained ML pipelines. MLeap is an open-source technology that allows
> Data Scientists and Engineers to deploy Spark-trained ML Pipelines and
> Models to a scoring engine instantly. The MLeap execution engine has no
> dependencies on a Spark context and the serialization format is entirely
> based on Protobuf 3 and JSON.
>
>
> The recent 0.5.0 release provides serialization and inference support for
> close to 100% of Spark transformers (we don’t yet support ALS and LDA).
>
>
> MLeap is open-source, take a look at our Github page:
>
> https://github.com/combust/mleap
>
>
> Or join the conversation on Gitter:
>
> https://gitter.im/combust/mleap
>
>
> We have a set of documentation to help get you started here:
>
> http://mleap-docs.combust.ml/
>
>
> We even have a set of demos, for training ML Pipelines and linear,
> logistic and random forest models:
>
> https://github.com/combust/mleap-demo
>
>
> Check out our latest MLeap-serving Docker image, which allows you to
> expose a REST interface to your Spark ML pipeline models:
>
> http://mleap-docs.combust.ml/mleap-serving/
>
>
> Several companies are using MLeap in production and even more are
> currently evaluating it. Take a look and tell us what you think! We hope to
> talk with you soon and welcome feedback/suggestions!
>
>
> Sincerely,
>
> Hollin and Mikhail
>

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