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.

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  1. Easier Web Service Publication

    At the moment the procedure for web service publication is not easy and intuitive. Most of time some Project Columns modules are needed after and before Score module in order to tell what column is target (response) and what columns in dataset must be considered as input. It must be easier in a visual surface than the programming environment like R to do this. But at the moment it is not the case with AzureML. After the recent update to publishing web service procedure, the result web service considers all the columns of input dataset as input parameter! So my…

    3 votes
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  2. Trial Period Question

    I'm enjoying Azure ML and the samples provided. After the 30 day trial do the samples remain or to we loose them?

    Also, after the 30 day free trial, what changes? Do we still have the account and all the existing experiments? Then do we just have to pay for running experiments?

    1 vote
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  3. save experiments

    Have the option to choose which workspace to save an experiment to as well as giving it a name. Currently the only way to move an experiment is to cut and paste all the objects in it into an empty experiment in another workspace.
    thx

    1 vote
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  4. sample

    Thank you for the samples. How do we get more info about the sample data? There seems to be a Sample Section missing from ML Home page or the Info links are missing directly from the sample in Studion.

    1 vote
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  5. Web service executions should appear in the Run History complete with all logs

    As far as I can tell there is no way to retrieve logs for runs triggered from web services.

    Having them alongside the ML Studio executions in the run history would be great (a column indicating whether the run was triggered from ML studio or from a web service would be nice as well).

    Another possibility (or even better - in addition) would be to dump the logs into a blob storage container in the associated Azure account, similar to Azure Website logs.

    5 votes
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  6. No "Ready For Production?" button

    At the end of the tutorial for the German Credit Risk data, I couldn't locate the "Ready For Production?" button. Did I miss something, was it moved?

    I love this site. Thank you for the opportunity to practice.

    1 vote
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  7. Support online learning for recommender

    It looks like Matchbox recommender doesn't support online learning at the moment. This makes impossible to provide recommendation for the new users based on their profile/preferences.

    44 votes
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  8. Allow R Node to make Internet calls and read Plain Text

    Most financial data is available on the Internet - this includes equities, derivatives prices, economic data etc. All of these are in different formats and don't always come in neat CSV formats.

    What we need in Azure ML is the freedom to read plain text, HTML or other formats as is. We can write the R Code to parse it into datasets internally. This will hugely improve the usability of the platform.

    5 votes
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  9. Provide support to upload compressed datasets

    It would be great if we are allowed to upload a ZIP file containing a TXT or CSV dataset. This will save on bandwidth and time for end users. Currently I can upload a ZIP file but I am unable to visualize that as a normal dataset.

    58 votes
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  10. Automate call center handeling

    Use machine learning to redirect an incoming voice call (with speech recognition) to a self-service portal instead of an agent

    1 vote
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  11. Machine Learning Workspaces

    Looking though the new portal, there are many cool things. However, I haven't been able to find a way to access my AzureML workspaces from the new portal

    29 votes
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  12. "trained modele"

    Allow getting the Original Experiment from the trained model.

    After you saved train model as a trained model, you can delete/change the original experiment.
    Being able to see the original Experiment the model is based on (with the right permissions), would help retain the knowledge.
    On the same issue, if the original experiment exist, then some indication on the train model was saved as Trained Model similar to set/unset publish input/output.

    5 votes
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  13. Save R-Script as trained model

    Currently only built-in models in Azure ML can be saved and published. We've built a model in R and want to publish it as well but Azure ML does not support it right now. I wonder if Azure ML can somehow put some rules on the input/output of the R-Script, so when a script follows these rules, it can be saved and published like any other built-in models. This could increase the extensibility and flexibility of Azure ML pretty much.

    120 votes
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  14. Run only part of a model

    When building a model, running it takes quite some time and while working on it, I may not have fully specified all elements of my model as I create the outline of the proces.

    Therefore I would like to be able to run the model up to a certain step, ignoring all elements after the selected block. This would save compute and wait-time and would fit my way of working nicely.

    61 votes
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    3 comments  ·  Flag idea as inappropriate…  ·  Admin →
  15. allow to access the features I signed up for when I sign up!

    I have just signed up for a trial of Azure Machine Learning, yet your site keesp telling me either: 1. My account does not exist, or 2. That I do not have access to the ML workspace I just created (with the account that apparently does not exist!).
    A typically clunky Microsoft experience, I am afraid...

    1 vote
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  16. Learning materials could use improvement

    It would be great to see a public competition such as http://www.kaggle.com/c/titanic-gettingStarted used as the training content for learning AzureML.

    6 votes
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  17. Budgeting for ML

    Consumption pricing is very clear on the website but it would be great to 'predict' budget needs. Please publish examples of costs expected or being experienced by preview customers as soon as you can.

    6 votes
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  18. Annotation in Experiment

    It would be nice to see Annotation capability in Experiment. That will allow users to put notes with free form text explaining purpose of the module and how it works, etc..

    12 votes
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  19. Enable and Disable Steps in an Experiment

    When experimenting, the ability to disable steps makes it easier to try different approaches. For example, I wanted to have different sets of columns as inputs to a regression. I have 4-5 different Project Column steps with different fields and swap the output to the inputs to select. However, I'd love to just disable them on a right-click menu item.

    111 votes
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  20. It would be great to have access to all the Python as well as R

    I'm not familiar with R and don't wish to invest in learning it, when Python packages such as Scipy, Numpy, Pandas and Scikit-Learn meet most of my needs. I wish I could combine the power of these with Azure ML's slick interface, and easy-to-deploy APIs

    41 votes
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