Gopi Kumar (MSFT)

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  1. 2 votes
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    2 comments  ·  Data Science VM » Tools and applications  ·  Flag idea as inappropriate…  ·  Admin →
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    Gopi Kumar (MSFT) commented  · 

    We now have Windows Server 2016 version of DSVM which uses Python 3.6 as default.

  2. 1 vote
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    1 comment  ·  Data Science VM » Getting started  ·  Flag idea as inappropriate…  ·  Admin →
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    Gopi Kumar (MSFT) commented  · 

    Keras should be in the Python 3 environment on Windows 2016, CentOS and Ubuntu DSVM. Are you using the Windows 2012 edition of the DSVM? Pl so we would recommend moving to Windows 2016 edition if it is feasible for you.

  3. 2 votes
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    2 comments  ·  Data Science VM » VM deployment  ·  Flag idea as inappropriate…  ·  Admin →
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    Gopi Kumar (MSFT) commented  · 

    I agree this can be a bit confusing. To slightly mitigate that, we have created a "Deep Learning Virtual Machine" or the DLVM template (http://aka.ms/dlvm) that tries to simplify this. The DLVM uses exactly the same underlying VM image as DSVM (with all prebuilt GPU drivers, Deep learning frameworks etc plus a few extra end to end samples) but unlike DSVM, the DLVM can only be deployed on the GPU class machines (NC Series, ND Series) on Azure. There is still a challenge of choosing the correct region that we were not able to take care fully. We will explore further and see how we can simplify this. Thanks for the feedback.

  4. 7 votes
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    2 comments  ·  Data Science VM » Tools and applications  ·  Flag idea as inappropriate…  ·  Admin →
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    Gopi Kumar (MSFT) commented  · 

    Thanks for the suggestion and details of your scenario. Some of the ones in the list above are already available - Weka, Spark MLLib and H2O. Here is a more detailed list of salient tools available (still not 100% exhaustive!):

    https://docs.microsoft.com/azure/machine-learning/data-science-virtual-machine/overview#whats-included-in-the-data-science-vm

    We also have docker engine, nvidia-docker built into the DSVM. So you can bring in containers to run on the DSVM and can leverage GPU hardware if needed.

    We will evaluate what it would take to offer some of the other frameworks.

    Also with the momentum behind frameworks like Tensorflow, Torch etc for deep learning and ability to export models in standard way with ONNX to run the inferencing on a variety of run time natively (like WinML for Windows), hopefully the integration with backends including Java, C++ will become more easier from what are seeing in terms of developments in the broader ML/AI industry.

    Please do chime in with votes for specific tools to help us decide.

  5. 4 votes
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    2 comments  ·  Data Science VM » Tools and applications  ·  Flag idea as inappropriate…  ·  Admin →
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    Gopi Kumar (MSFT) commented  · 

    We update VMs roughly every 2 months or so. There is no fixed schedule.

  6. 1 vote
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    1 comment  ·  Data Science VM  ·  Flag idea as inappropriate…  ·  Admin →
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    Gopi Kumar (MSFT) commented  · 

    Thanks for reporting Akshay. Please use our forum http://aka.ms/dsvm/forum for product issues/questions and provide info on the version of RStudio, Linux edition (CentOS, Ubuntu), when you created the Data Science VM and any error message. This site is for mainly for new feature requests.

  7. 13 votes
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    0 comments  ·  Data Lake  ·  Flag idea as inappropriate…  ·  Admin →
    Gopi Kumar (MSFT) supported this idea  · 

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