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. Export Azure ML Visual Interface experiments to Python

    To make the visual UI really useful, it would be great to support export of Azure ML Visual Interface experiments to Python.
    The same applies to the Automated ML UI.

    53 votes
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    2 comments  ·  Flag idea as inappropriate…  ·  Admin →

    Hi Azure Customer,

    We have the plan for AutoML. But currently it is not in the roadmap for visual interface. We will be watching for additional upvotes for future priority considerations. Thank you for your feedback and understanding.

    Regards,
    Azure CXP Community

  2. We need to build in algorithms for Multi-label classification. Currently we do not support any of BP-MLL or ML-kNN etc.

    There are no support for Multi label classification by default in ML services. Users have to write their own code in Python/R or any language and go ahead with an ensemble of models. Why dont we have any support by default?

    33 votes
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    0 comments  ·  Flag idea as inappropriate…  ·  Admin →
  3. Share notebook VM

    Is it possible for 2 users of an AML Workspace to access the same notebook VM? We are both collaborators in the workspace, but my colleague cannot access the notebook VM I created.

    28 votes
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    1 comment  ·  Flag idea as inappropriate…  ·  Admin →
  4. Segregate a Workspace across multiple projects.

    Allow us to organize 1 workspace in several projects, allowing greater governance and cost sharing between projects.
    In this case, make it possible for us to create project folders where each folder / project has its associated objects, where we can implement access profiles for its objects.
    We would continue sharing processing clusters, but we could segregate registered models, pipelines, datasets, etc. by project folders.

    Today, as it is, we only achieved this segregation by assigning 1 workspace for each project.
    And this strategy of 1 workspace per project will make projects more expensive, because today, a trainning cluster cannot…

    22 votes
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    0 comments  ·  Flag idea as inappropriate…  ·  Admin →
  5. 22 votes
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    0 comments  ·  Flag idea as inappropriate…  ·  Admin →
  6. Enable GPU support when deploying to Azure Container Instances

    Azure Container Instances can be configured to provide GPU resources to the container (https://docs.microsoft.com/en-us/azure/container-instances/container-instances-gpu). However, there is no way to ask for GPU resources when deploying ML services via the Azure ML SDK (AciWebservice.deployconfiguration) or Azure CLI (az ml service create aci). Even if the image is built with GPU support enabled (ContainerImage.imageconfiguration(enable_gpu=True,...)), the image does not work properly in ACI because the GPU resources are not present.

    Please extend the SDK and CLI to allow specifying the GPU count and SKU when deploying to ACI.

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

    Hi Azure Customer,

    Thank you for your feedback. This feature is currently not planned mainly because ACI doesn’t have full GPU support yet. We will follow up with ACI team and expose it when they add full support. At the meantime, we will keep this feedback and vote opening.

    Thank you for your understanding.

    Regards,
    Azure CXP Community

  7. Add detailed model training progress information in Machine Learning Studio experiment view

    At now, the only training progress indicator in experiment view is a time elapsed counter. The idea is to extend number and types of possible counters while the model is being trained. Such information could possibly be: current training iteration, progress percentage, etc.

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

    Hi Azure Customer,

    After internal review, this feature request is not currently in the roadmap. We will keep this feedback open and watching for additional upvotes for future priority considerations. Thank you for your feedback again ^^

    Regards,
    Azure CXP Community

  8. Allow ACI and AKS containers to assume a managed identity role

    Currently, there's no way for an ACI or AKS-instanced AML program to assume a role. We would like to access other Azure resources with our AML code, so we would like for the containers created to be able to assume an existing role, using the normal procedures.

    9 votes
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    0 comments  ·  Flag idea as inappropriate…  ·  Admin →
  9. Need Sample for Azure ml pipeline yaml template

    Looking Sample Project for Azure CLI ML Pipeline create from Yaml Template, Please share sample for it.
    https://github.com/MicrosoftDocs/pipelines-azureml/tree/master/ml-pipeline-yml
    az ml pipeline create -n mypipeline -y mypipeline.yml
    https://docs.microsoft.com/en-us/azure/machine-learning/service/reference-pipeline-yaml

    8 votes
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    0 comments  ·  Flag idea as inappropriate…  ·  Admin →
  10. Add segmentation to data labeling tool

    You have bounding box labeling but not anything to help with segmentation.

    7 votes
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    0 comments  ·  Flag idea as inappropriate…  ·  Admin →
  11. Sharing compute instance in members of same developer team

    Actually compute instance can only be used by one member of team, and others developers can't use this.

    A good feature it's all members of a workspace can use compute instance (with the right rights), and make a queue of experiments runnings.

    7 votes
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    0 comments  ·  Flag idea as inappropriate…  ·  Admin →
  12. Add PowerShell to Azure Notebooks

    Please add and improve the kernel for Windows PowerShell/Powershell Core/6/7 to Azure Notebooks.
    PowerShell should be treated as first citizen language and there are a lot of usecases for teaching with Azure Notebooks.
    Alternatively provide an option to load custom kernels.

    7 votes
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    0 comments  ·  Flag idea as inappropriate…  ·  Admin →
  13. Monitor AML Cluster performace

    Add to AML Python SDK functions to monitor AML compute cluster's load/performance (CPU, Mem, Disk I/O, Network, GPU).

    6 votes
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    0 comments  ·  Flag idea as inappropriate…  ·  Admin →
  14. Deploy same name service in Azure machine learning workspace service.

    In Aml workspace, we are allowed to add multiple Compute assets for a type. Ideally ml services should able be deploy on both AKS cluster but due to some reason, same named service can't be maintain in Deployment asserts. For example, I can have two AKS Compute resource in a workspace named as AKS1 and AKS2 and service named as 'intelligentAgent'. This service can be deploy in AKS1 but I have trouble deploying same service in AKS2.

    I need to do this to maintain services for BCP and disaster recovery.

    Could you please allow same named services on different AKS…

    5 votes
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    1 comment  ·  Flag idea as inappropriate…  ·  Admin →
  15. Provide a means to recover code when one of the workspace resources is deleted

    When a core resource for the ML workspace is deleted, the workspace can no longer retrieve any code. Creating a means to be able to resync a new resource and retrieve the code, or implementing a backup would be another solution.

    5 votes
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    0 comments  ·  Flag idea as inappropriate…  ·  Admin →
  16. Remove AKS minimum core restriction ("cluster_purpose")

    If I want to attach an AKS cluster in development environments that don't meet the 4 agents / 12 core requirements, I need to set the "clusterpurpose = AksCompute.ClusterPurpose.DEVTEST" parameter via the Python API. However, this parameter is not supported in ARM templates and also not in the Azure CLI extension, so this complicates our automation strategy.

    The minimum requirements for running an AKS cluster in production are well documented, so it shouldn't be up to the "Machine Learning service" to enforce any restrictions.

    Having this "cluster_purpose" parameter is just an unnecessary complication, and should therefore be removed…

    5 votes
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    0 comments  ·  Flag idea as inappropriate…  ·  Admin →
  17. Support Python 3.6

    Please support Python 3.6

    4 votes
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  18. Azure Machine Learning Studio should be supported for touchscreen use

    Azure Machine Learning Studio requires use of a computer with a mouse for Drag and Drop. One cannot drag using an iPad touch screen for example.
    This may require an app for IOS and a corresponding one for Android devices to enable ML Studio to be supported by devices.

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

    Hello Azure Customer,

    Thank you for your feedback, your feedback is very important for us and we hear you. This feedback is currently not been prioritized for implementation. As we get more upvotes , we will again access it and may include in our future implementation plans.

    Thank you for understanding.
    Azure CXP Community

  19. 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

    4 votes
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    0 comments  ·  Flag idea as inappropriate…  ·  Admin →
  20. 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.

    4 votes
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