Machine Learning

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How can we improve Microsoft Azure Machine Learning?

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  1. Underlying storage account for Machine Learning Service Workspace should be HTTPS only

    Currently the MLSW triggers Azure security toolkit & security center alarms because the default configuration of underlying storage account allows http traffic.

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

  2. Allow Properties Shared by Multiple Items to be Edited In a Single Place

    If I select several items in an Azure ML Studio experiement that all share a common property, I should be able to set that property in one place - once - and not have to edit each item separately.

    A huge portion of what data scientist are doing in an experiment is trying out different classification algorithms, training them, scoring them, and evaluating and comparing results. This makes for a lot of repetitive, monotonous work. And it means we have to do exactly the same edits (like setting a dependent variable) across a bunch of different items.

    There's no reason…

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

  3. Need hyper parameter tuning for ML models

    Should allow to tune hyper parameters in order to improve algorithm performance. Implement Grid search, Randomized Search and Hyperopt for parameter tuning.

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

  4. All Advanced Time Series models are not present in Azure ML.

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

  5. Support Named Entity Recognition labeling

    It would be great if can label Named Entities. Ideally we should be able to export it in different formats like BIO-notation,..

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

  6. How to save ContainerEvents for model-deployed ACI

    Can't save ContainerEvent to Log Analytics because Azure ML can't create logging-enabled containers. It would be better to be able to get the following logs.

    https://docs.microsoft.com/en-us/azure/container-instances/container-instances-log-analytics#view-events

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

  7. About LSTM and 3D tensors dataset support for Auto ML

    Will Auto ML support the LSTM algorithm in the future?
    Would also be nice to be able to support 3D tensors dataset.

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

  8. "az ml run show -r runid" pops surprised output

    When I am using command "az ml run show -r runid",
    This the output:

    az ml run show -r b4c190b4-fd00-43ca-bf31-639221a9485c
    Error, default experiment not set and experiment name parameter not provided.
    Please provide a value for the experiment name parameter.

    The problem is I can't provide experiment name, that's the information I want to query for...

    Could we refine this command? I can provide -w workspace instead.

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

  9. How to integrate DevOps approach with VM Notebook in AMLS ?

    Today, the platform is amazingly evolving in term of integration. We can now monitor and manage almost everything in the visual interface.

    My question is how can we improve even more this experience by adding the DevOps part (instead of having to go threw Azure Notebooks, or Visual Studio) to the Notebook VM and Jupyter environment.

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

  10. More informative error message when building the docker image fails.

    I was trying to deploy a scoring pipeline on Azure using AML SDK in Python. The scoring pipeline needs fbprophet library to train the forecasting model on the fly, and forecast for the future. I added fbprophet into the pip install in the myenv.yml by using myenv.addpippackage("fbprophet"). Then, the step of building the image failed.
    The error message did not have any information helpful for debugging. Although there might be somewhere with more detailed logs, but I had no clue where to find the logs. I had to google around for any possible reason.

    After being blocked by…

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

  11. Data Explorer / Kusto as Dataset in AML

    We're already using Data Explorer as a way of accessing data from a data lake for a number of other applications. It seems a perfect match for machine learning datasets, with the data already tabularized and often cached. The available alternative is to read the files, but presumably this doubles up on the processing already done by DE.

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

  12. Allow for filtering to experiment / error type granularity in Azure Monitoring

    Allow for filtering to experiment granularity in Azure Monitoring.

    Currently metrics only send value 1 if send to Azure Monitoring e.g. if an experiment run succeeds. During experimentation the larger share of experiments will fail, so we need to understand both the error type and the specific experiment at least.

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

  13. 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 →

  14. Azure ML Chain

    Most of the real life applications of ML need layered chained algorithms wherein output of one algorithm will be fed into input of another.

    Can we see new module in Azure ML for Chain models to choose from in a drag and drop fashion.

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

  15. Add Script bundle input to Create Python Model module

    Hi,
    would be useful to have Script bundle input as in Execute Python Script for more advanced training.
    Pavel.

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

  16. 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…

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

  17. Update SQLite version

    Currently, it seems that the Apply SQL Transformation module uses SQLite version 3.8.6. Could you update it newer one? As of 2019/05/01, the newest version is 3.28.0. It supports new SQL feature like window function, some useful extensions like Geopoly, and many performance enhancements.

    2 votes
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    triaged  ·  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. Gantt view of all experiments execution in Machine Learning Workspace

    To see a Gantt chart of the time consumed by each of the experiments running simultaneously in the ML.

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

  20. 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…

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