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Microsoft Machine Learning Server Samples and Solutions

Microsoft Machine Learning Server supports R and Python deployments on Windows, Linux and Hadoop. See the Machine Learning server documentation for more information about supported platforms.

Microsoft Machine Learning Services brings the compute to the data by allowing R or Python to run on the same computer as the database. It includes the Trusted Launchpad service, which runs outside the SQL Server process and communicates securely with the R or Python runtime.

Use the MSDN Forum Microsoft Machine Learning Server for questions about ML Server. If you have questions about the samples and solutions, please open an issue in the relevant repository.

This repository serves as a landing page for you to more easily find the samples and solutions in other repositories. Please create a pull request if you have a repository you'd like to add to this list.

Samples

The following repositories contain sample code for you to try.

RepositoryDescription
Microsoft/SQL-Server-R-Services-SamplesSamples on how to use SQL Server ML Services with R.
Microsoft/ML-Server-Python-SamplesPython Samples for ML Server
Microsoft/microsoft-rOperationalization and the MicrosoftML package

Direct links to all the samples and solutions offered are below. They may contain multiple languages and/or platform code.

SolutionDocumentationLanguages
Binary Classification (1)CodePython
Binary Classification (2)DocumentationPython
Campaign OptimizationWebsiteR
Categorical featuresCodePython
Customer ChurnRepositoryR
Energy Demand ForecastingRepositoryR
Feature selectionCodePython
FormulasCodePython
Fraud DetectionWebsiteR
Galaxy ClassificationRepositoryR
Hyperparameter tuningCodePython
Image classificationCodePython
Image similarityCodePython
Input schemasCodePython
Length of StayWebsiteRPython
Loss functionCodePython
Multi-class classificationCodePython
Image SimilarityWebsitePython
Loan ChargeOff PredictionWebsiteR
Loan Credit RiskWebsiteR
Predictive Maintenance (1)RepositoryR
Predictive Maintenance (2)RepositoryR
Product Cross SellRepositoryR
Regression with MicrosoftMLCodePython
Regression with RevoscalePyCodePython
Resume MatchingRepositoryR
Retail ForecastingRepositoryR
Sentiment AnalysisCodePython
Text ClassificationWebsiteRPython
Text FeaturizationCodePython

Contributing

Please create a pull request if you have a repository you'd like to add to this list.

This project welcomes contributions and suggestions. Most contributions require you to agree to a Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us the rights to use your contribution. For details, visit https://cla.microsoft.com.

When you submit a pull request, a CLA-bot will automatically determine whether you need to provide a CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions provided by the bot. You will only need to do this once across all repos using our CLA.

This project has adopted the Microsoft Open Source Code of Conduct. For more information see the Code of Conduct FAQ or contact opencode@microsoft.com with any additional questions or comments.

Legal Notices

Microsoft and any contributors grant you a license to the Microsoft documentation and other content in this repository under the Creative Commons Attribution 4.0 International Public License, see the LICENSE file, and grant you a license to any code in the repository under the MIT License, see the LICENSE-CODE file.

Microsoft, Windows, Microsoft Azure and/or other Microsoft products and services referenced in the documentation may be either trademarks or registered trademarks of Microsoft in the United States and/or other countries. The licenses for this project do not grant you rights to use any Microsoft names, logos, or trademarks. Microsoft's general trademark guidelines can be found at http://go.microsoft.com/fwlink/?LinkID=254653.

Privacy information can be found at https://privacy.microsoft.com/en-us/

Microsoft and any contributors reserve all others rights, whether under their respective copyrights, patents, or trademarks, whether by implication, estoppel or otherwise.

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