Machine Learning

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Azure Machine Learning enables developers and data scientists to build advanced analytic web services in minutes and hours, eliminating the heavy lifting associated with deploying machine learning in modern data driven applications.

How can we improve Microsoft Azure Machine Learning?

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  1. F# Support in Azure ML

    Azure ML is great. I would like Azure ML to support F# -> with both the code sample gen (currently C#) and the script support (currently R).

    874 votes
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    12 comments  ·  Flag idea as inappropriate…  ·  Admin →
  2. C# Support in Azure ML

    Support C# Execution modules. While R and Python are useful in certain situations, C# is useful also. Given the large number of developers who know C# as opposed to R, this opens custom modules to a much wider audience.

    217 votes
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    2 comments  ·  Flag idea as inappropriate…  ·  Admin →
  3. Add Machine Learing to Azure Stack

    Request: Add AzureML as part of Azure stack

    Rationale
    Interest in ML is on the rise Many companies are thinking of ML pilots.. Now ML usecases many times use ainternal documents e.g claims documents. IMO many organizations will take 2-5 years to grapple with the security/privacy concerns. In the mean time , it will help the organizations start ML pilot projects if AzureML is made available in AzureStack for on premise trials.

    Azure ML currently is one of the most attractive destination for anyone to pilot with. It brings SAS like drag and drop capabilities. Has a much more complete…

    181 votes
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    0 comments  ·  Flag idea as inappropriate…  ·  Admin →
  4. Import data from Azure Data Lake Store

    Right now you can access files on Azure Data Lake Store through a Hive cluster, which is both expensive and hard to set up. Azure ML should have direct access to Azure Data Lake Store files.

    180 votes
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    5 comments  ·  Flag idea as inappropriate…  ·  Admin →
  5. Support more recent versions of R

    AzureML currently support only old versions of R:
    * CRAN R 3.1.0, released in 2014
    * Microsoft R Open 3.2.2, released in 2016

    Some R packages are not available in these older versions, or in some cases the package is available but it is an older version of the package with incompatible differences with the newer version.

    Several newer versions of both CRAN R and Microsoft R are available. AzureML should support them. Also, going forward, there shouldn't be such a considerable delay between R major version releases and their availability in AzureML

    174 votes
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    8 comments  ·  Flag idea as inappropriate…  ·  Admin →
  6. Time series models

    Would love to see a time series prediction model using a MultiClass Neural Net. Also, where's the N# documentation?

    173 votes
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    6 comments  ·  Flag idea as inappropriate…  ·  Admin →
  7. Add Package ‘Relaimpo’

    This is a critical package in calculating the relative impact of the components in a multivariate regression model.

    122 votes
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    under review  ·  0 comments  ·  Flag idea as inappropriate…  ·  Admin →
  8. Azure ML support for DocumentDB

    I wish to implement a project using the new DocumentDB service offered by Azure, which eventually I wish to apply machine learning on the dataset. However, I understand that Azure ML does not currently support ingressing from DocumentDB. Would Azure ML be supporting the ingressing of DocumentDB soon, as this would be the deciding factor on my decision on whether to use DocumentDB or not eventhough the DocumentDB is the ideal datastore implementation for the project. If Microsoft Azure ML be offering the same tight and first class integration for DocumentDB as it does for the other Microsoft datastore options,…

    120 votes
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    3 comments  ·  Flag idea as inappropriate…  ·  Admin →
  9. Enable odbc connection from "Excute python script" module

    Odbc drivers are not installed on machines running the python script. Solving this will enable users to create their own Reader module by using their own business logic to access azure sql.

    119 votes
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    4 comments  ·  Flag idea as inappropriate…  ·  Admin →
  10. Support JSON for input/output

    Several custom algorithms I use are designed expecting input in JSON format. This is ideal for integrating with a web service, but unfortunately ML Azure doesn't seem to support it.

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

    JSON parsing is not yet implemented as a separate module. As a workaround for JSON parsing, you could use Execute R Script in following manner:

    1. Compress the JSON file as zip package and upload to ML Studio as .zip format file.

    2. Connect the .zip file to Execute R Script rightmost port

    3. Execute following R script (replace “sample_json.txt” with your file name).

    library(RJSONIO)
    library(plyr)
    data.set = ldply(fromJSON(content=“src/sample_json.txt”))
    maml.mapOutputPort(“data.set”);

    Note that this assumes your JSON file holds an array of similar records.

  11. 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…

    84 votes
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    0 comments  ·  Flag idea as inappropriate…  ·  Admin →
  12. Azure ML Integration with Tableau, Qlikview & PowerBI

    Many visual IDEs for Machine Learning are fast growing today.
    They provide a way a mechanism to directly process data and enable consumption of data in popular BI tools. This should be done for Azure ML as well

    73 votes
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    3 comments  ·  Flag idea as inappropriate…  ·  Admin →
  13. Ensemble Models in Azure ML Studio

    It would be great if in an Azure ML Experiment I could ensemble (with personalized weights) different Models; such as, Neural Networks with Desicion trees.

    So far, I've only make this manually using a Python script to average the outputs of the models I want to ensemble. But since the python script module only takes 2 dataframas as inputs it takes a lot of scripts to make a big ensemble between 4 or 5 models

    67 votes
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    1 comment  ·  Flag idea as inappropriate…  ·  Admin →
  14. Training with very large dataset in not works

    I was trying to create an experiment with the Netflix Prize dataset that contains about 100 Milions of records, and after uploadin the 2.6GB csv file and run the training on that, it fails due to out of memory exceeded exception

    63 votes
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    1 comment  ·  Flag idea as inappropriate…  ·  Admin →
  15. Configurable timeout for experiments and web services

    Some bugs/errors could cause experiments or web service to run longer than expected. This can lead to high costs if several executions never ends.
    There should be configurable timeouts, so that any run that exceeds this timeout is terminated:

    - Workspace global timeout: applies to all experiments and web services in a workspace
    - Experiment and web-service specific timeouts

    62 votes
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    2 comments  ·  Flag idea as inappropriate…  ·  Admin →
  16. Allow reading line seperated json format from blob storage

    We're using Stream analytics to write results in a line seperated json format, which is a standard for many other services, but it is impossible to read it from blob storage.
    the workaround suggested will not help when using prediction experiment and getting the data from blob in a realtime manner

    61 votes
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    1 comment  ·  Flag idea as inappropriate…  ·  Admin →
  17. 61 votes
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    4 comments  ·  Flag idea as inappropriate…  ·  Admin →
  18. Multiple inputs for Evaluate Model (only 2 currently possible)

    Would be easier to work with & compare multiple models. having to cross-pairing all models is too slow to design & hard to evaluate.

    Even if the output when multiple models would have fewer features than the default 2 input evaluate. (ex: fewer visualization options, metrics) But at least a good subset of main evaluation metrics should be visible.

    57 votes
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    1 comment  ·  Flag idea as inappropriate…  ·  Admin →
  19. Allow Azure Table Access with SAS Authentication

    Currently only one storage account can be associated to an ML workspace, leaving SAS authentication as the only option to access other storage accounts. Nevertheless, testing the documented SAS access returns the comment:

    [ModuleOutput] Azure Table with SAS Uri not implemented yet.

    Implementing this feature, thus allowing access to multiple storage account, would widely increase the flexibility and applicability of ML to big data solutions.

    57 votes
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    0 comments  ·  Flag idea as inappropriate…  ·  Admin →
  20. Add LightGMB as a module within Studio ML

    A lot of the newer Algos require R or Python scripts to execute. LightGMB was built within Microsoft. It would be great if this could be added as a module within Studio ML rather than requiring R or Python.

    https://github.com/Microsoft/LightGBM/issues

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