Machine Learning

Welcome! The Azure Machine Learning team invites you to share and vote for features to help you build, manage, and deploy custom machine learning models.

Have a technical question, or want to learn more? Please visit our documentation, MSDN forum or StackOverflow.


  1. Default compute target

    An awesome feature has been added to the new Visual interface: when I want to run my experiment, I have to specify what kind of machine I want to run it on.

    When the experiment has to run more than once, I found only one – tiny bit – annoying feature: every time you run the experiment, you have to choose a compute target. What if I want to use the same target for the next few days, or even longer?

    I wish there was a possibility to set a default size, and use that, unless I want to scale…

    3 votes
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  2. Need drop-out parameter for neural network

    The neural network for custom script should put a dropout rate parameter or at least tell us the code for doing dropout in the custom script. Thanks

    3 votes
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  3. Need a module to identify Low / High Correlated feature with Target Variable as well as High Correlated input features.

    A new module which outputs High/low Correlated input features with Target Variable as well as to identify High correlated input features.

    This module would help to create better Trained Data Set and that would turn to create better ML model.

    3 votes
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  4. Resync Keys

    It is very said we need manually "Resync Keys" in ML studio. We can not even find a API to call resync key in power-shell.

    3 votes
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    0 comments  ·  Flag idea as inappropriate…  ·  Admin →

    Hi Azure Customer,

    Thank you for your feedback here. Since Azure Machine Learning Studio will be deprecated. We will not be supporting in Studio, investigtaing how Resync Keys works with visual interface

    We will get back to you soon once we have any update.

    Thank you for your understanding.

    Regards,
    Azure CXP Community

  5. Be able to write results to SQL tables through Datasets and Datastores

    Currently it doesn't look like it is possible to directly upload the results of a batch Azure ML job to a SQL database that has been registered within the workspace as a datastore. The SQLDataReference class exists, but none of the methods work: https://docs.microsoft.com/en-us/python/api/azureml-core/azureml.data.sqldatareference.sqldatareference?view=azure-ml-py

    It would be great to be able to easily write ML results to SQL databases that the service principal has write access to.

    3 votes
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  6. model_data_collection should log failed API request too

    We plan to leverage modeldatacollection message type in traces to log our API request payload (instead of printing the payload to STDOUT) only to realize that failed requests were not logged. It's actually more useful to log payload for failed requests so we can reproduce the issue rapidly.

    3 votes
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  7. Enable Machine Learning Studio for Government Cloud

    Please enable azure machine learning services for government cloud customers

    Currently there is no timeline for releasing ML services to Gov Cloud users, but we are interested in the service.

    https://azure.microsoft.com/en-us/global-infrastructure/services/?products=machine-learning-studio

    3 votes
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  8. Add the AzureSMR R package with support to HTTPS

    Could be very useful interact directly into a R Script with azure resources (example: storage account, blob, ecc...)

    3 votes
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    1 comment  ·  Flag idea as inappropriate…  ·  Admin →

    Dear Azure Customer,

    Thanks for the feedback. Your feedback is very important to us. Our engineering team will investigate it and consider your feedback seriously. We will get back to you soon.

    Thank you for understanding.
    Azure CXP Community

  9. Deploy the model to Azure Functions in the Designer

    There is a request to deploy a designer-generated model to Azure Functions. Are there any plans for future development?

    3 votes
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  10. Increase arbitrarily small metrics document limit (3000b)

    Remove the 3000b limit for metrics:

    azureml._restclient.exceptions.ServiceException: ServiceException:

    Code: 400
    
    Message: (ValidationError) Metric Document is too large, 3195b is larger than the max metric size 3000b.
    Details:
    Metric Document is too large, 3195b is larger than the max metric size 3000b.

    This is from running .log_table with only 5 integers (and associated short strings)

    3 votes
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  11. Support python 3.7

    Support running Python 3.7 scripts

    3 votes
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  12. Edit or remove experiments in Automated Machine Learning

    I just tried the Automated Machine Learning service with one of my older projects, simply out of curiosity.

    I created an experiment, with a compute setup, and then I wanted to add another compute instead. The only way it can be done is by creating a new experiment with the same name, but a different compute setup.

    Should it be possible to simply edit the experiment that was generated previously from the dashboard?

    I can see, that there is an idea of keeping the previous run results, but when there is a cancelled run, or I cannot benefit from it,…

    3 votes
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  13. Please update Forecast package in Azure ML Studio

    The Forecast package on AZURE ML STUDIO needs to be updated. Can't Microsoft have a package update scheduled every month or so?

    3 votes
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    0 comments  ·  Flag idea as inappropriate…  ·  Admin →

    Dear Azure Customer,

    Thanks for the feedback. Your feedback is very important to us. Our engineering team will investigate it and consider your feedback seriously. We will get back to you soon.

    Thank you for understanding.
    Azure CXP Community

  14. 3 votes
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  15. Azure Policy Support for restricting SKU of AML Compute

    Today, Azure ML Compute does not honor Azure Policy Restrictions on VM SKUs

    I Created an Azure Policy restricting VMs to a specific SKU(VM Size), assigned the Policy to resource group having Azure ML WorkSpace
    Still, I can create ML Compute using AzureML workspace for any size, including the size which is disallowed in the Policy
    Is this a bug or by design? I want to restrict the size of compute being created from AzureML

    3 votes
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    0 comments  ·  Flag idea as inappropriate…  ·  Admin →
  16. Link Dataset, Experiment, Image, Model, Deployement

    As part of managing the whole Data Science Process within Azure ML, is there a way to link a Dataset, an Experiment and related produced Image, Model and Deployment, apart from description.

    3 votes
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    2 comments  ·  Flag idea as inappropriate…  ·  Admin →
  17. Azure DevOps ML extension - bug when triggering release pipelines

    I have multiple release pipelines triggered by new model versions. Each pipeline uses different models, but with the same name (they are in different workspaces of the same resource group).

    The issue is that all pipelines seem to be triggered by the same model (the one in the oldest workspace), even though they're using different references, and different service connections. I expect them to be triggered by updates to their respective models, of course.

    I can provide more details if needed.

    3 votes
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  18. We need an example of using AutoML in Azure DevOps rather than a simple sklearn model in the Python MLOps example?

    Pelase Add good example in AzureDevOps using a video tutorial on your websiten rather than the MLOPs Python sample and how we can use it in Azure DevOps.

    3 votes
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  19. Need Token for words with Polish Language

    I would like to make an application that process polish sentence.

    3 votes
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  20. define and run pipeline using Logic App

    It's super make sense this type of workflow via GUI, not only code. Please refere the following service as well.


    • Azure DevOps

    • Azure Data Factory

    3 votes
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