Machine Learning

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How can we improve Microsoft Azure Machine Learning?

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  1. Add FQDN as a parameter in Azure ML Webservice.deploy_from_image/model

    An Azure ML web service deployed to ACI gives you an IP address to request response. However, this IP address can change on its own because of some Azure Internal Events on ACI.

    The Azure Container Instance (ACI) allows you to define a FQDN which binds to the underlying IP address so that you don't have to deal with the IP Address. However, it is proving impossible to update the Azure ML deployed ACI because of various issues. If FQDN can be added as a parameter in Webservice.deploy_from_image which binds to the ACI container's FQDN, this would solve all the…

    87 votes
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    0 comments  ·  Flag idea as inappropriate…  ·  Admin →
  2. Add Machine Learning services to use Azure AD Token

    When using Machine Learning's API, add a function that can authenticate with Azure AD Token

    14 votes
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    1 comment  ·  Flag idea as inappropriate…  ·  Admin →
  3. Need Advanced Time Series Models in AZURE ML like ARIMA, ARIMAZ, SARIMAX etc. for various industrial applications

    Time series models have numerous industrial applications and most widely used models in R & Python are ARIMA, ARIMAX, SARIMAX etc.
    Request to add all advanced time series models in Azure ML.

    13 votes
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    0 comments  ·  Flag idea as inappropriate…  ·  Admin →
  4. 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.deploy_configuration) or Azure CLI (az ml service create aci). Even if the image is built with GPU support enabled (ContainerImage.image_configuration(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.

    13 votes
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    1 comment  ·  Flag idea as inappropriate…  ·  Admin →
  5. Workspace ARM resource should repair missing permissions on other Azure objects (e.g. Key Vault)

    The Microsoft.MachineLearningServices/workspaces ARM resource should be able to fix missing permissions on Azure resources it depends on (such as Key Vault access policy) when it is redeployed.

    Currently, the ML Workspace creates a AAD Service Principal for itself and assigns it at least these permissions (and perhaps more) during provisioning:
    - Contributor access to the Resource Group
    - Contributor access to the Container Registry
    - an access policy in the Key Vault allowing all operations except Purge
    - Storage Blob Data Contributor access to the Storage Account

    However, if anything happens to these permissions (for example, the Key Vault access…

    11 votes
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    0 comments  ·  Flag idea as inappropriate…  ·  Admin →
  6. Open source the Azure ML SDK and CLI extension

    It would be great if the Azure ML SDK and CLI extension were open-sourced and put on GitHub (like several other Azure tools). The user community could help by fixing minor issues and adding improvements and the increased code transparency would help the users learn to use the tools correctly and understand their behavior.

    The Azure ML SDK and CLI extension are implemented in Python, so everyone has access to the source code anyway, but there is no way currently to contribute fixes to the original projects and determining the changes between versions is cumbersome.

    9 votes
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    0 comments  ·  Flag idea as inappropriate…  ·  Admin →
  7. Support Python 2.x

    Please support Python 2.x as many frameworks still use it.

    7 votes
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    0 comments  ·  Flag idea as inappropriate…  ·  Admin →
  8. improve new visual interface run execution performance (it's that bad...)

    ml studio was already slow, for the new visual is several times worst, even after creating the default 2 node cluster, things that took one minute on ml studio now go up to 8-10 mins on visual preview?understand the tracking happening below, cluster overhead and all that, but the point is, as it is, it's unusable, some screenshots ...
    https://twitter.com/rquintino/status/1126263499821387776

    7 votes
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    0 comments  ·  Flag idea as inappropriate…  ·  Admin →
  9. Ability to run experiments without using SSH port

    A lot of enterprise customers have concerns opening SSH port even with VNet enabled and using Azure ML service tag.

    We should find a way to run experiments on computes like DSVM without opening up access to SSH port.

    7 votes
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    0 comments  ·  Flag idea as inappropriate…  ·  Admin →
  10. 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.

    6 votes
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    triaged  ·  1 comment  ·  Flag idea as inappropriate…  ·  Admin →
  11. Role based access needed for Azure ML Service

    We have multiple customers asking for the following role based scenarios,

    - Experimentation: Define roles for users who can only submit the jobs, who can only manage computes etc.
    - Inferencing: Define roles as explained below,

    I’m trying to run a standard 3 env (build/test/live) set up with a single common AML Workspace (so that the immutable images tested are promoted, not re-created in a different Workspace instance).

    I’d need to be able to achieve the below:
    • Data Scientists can register models & create images within the AML Workspace
    • Data Scientists can deploy images to ACI or Build…

    5 votes
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    0 comments  ·  Flag idea as inappropriate…  ·  Admin →
  12. Please add function that notify some email when Experiment's Runs is failed

    I hope a function that notify some email when Experiment's Runs is failed.
    I can know whether there is error or not if I open their Experiment manually now.
    But when I run experiment automatically, I want to notify to some email if experiment's Run is failed.

    4 votes
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    0 comments  ·  Flag idea as inappropriate…  ·  Admin →
  13. Please add function that can install "CLI extension for Azure Machine Learning service" at Docker Azure CLI

    Please add function that can install "CLI extension for Azure Machine Learning service" at Docker Azure CLI

    4 votes
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    2 comments  ·  Flag idea as inappropriate…  ·  Admin →
  14. Export trained MAMLS models to standalone Runtime environment

    Need a way to run trained MAMLS models outside of MAMLS. Need a way to export MAMLS trained models to an external runtime environment.

    3 votes
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    0 comments  ·  Flag idea as inappropriate…  ·  Admin →
  15. Support custom R modules in the Visual Interface

    We have a client with a large codebase in R that we want to migrate from SPSS to Azure Machine Learning. Right now we're stuck with AML Studio which doesn't give us the performance that we need for running experiments.

    3 votes
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    1 comment  ·  Flag idea as inappropriate…  ·  Admin →
  16. PYTHON into Azure

    Would be great to see Microsoft investing in Python, in order to embedded it into the Azure Machine Learning.

    2 votes
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    0 comments  ·  Flag idea as inappropriate…  ·  Admin →
  17. 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...)

    2 votes
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    1 comment  ·  Flag idea as inappropriate…  ·  Admin →
  18. Option to allow training for more than 24 hours

    The utilities available in ML Studio is really convenient for me, however my dataset (around 1m rows) is taking too long to train, and I am only using a 2 layer FC NN. I think most of us won't mind paying for it.

    2 votes
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    triaged  ·  3 comments  ·  Flag idea as inappropriate…  ·  Admin →
  19. Migration from Azure Machine Learning Studio to Visual Interface

    Ideally this should be done automatically for us, but I'd be happy with an export/import flow that lets us migrate manually.

    2 votes
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  20. Add possibility to pass parameters to scoring script when deploying an image

    When deploying an image to AML Service, the path of the scoring script is given to the method using the execution_script parameter: ContainerImage.image_configuration(execution_script='score.py', ...). However, there is no argument for passing values to script parameters, which are needed in the init() function to do stuff like fetching passwords from Key Vault and getting sample data for the schema.

    Please add the possibility to pass parameters to the scoring script when deploying and image to AML Service. For example, when creating a Python script step in an AML Pipeline, we can add these parameters as follows: PythonScriptStep(script_name='train.py', arguments=['--workspace_name', 'MyWS', '--model_path', './my_model.pk'].…

    2 votes
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