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docs/machine-learning/python/ref-py-microsoftml.md

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---
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title: microsoftml Python package
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description: Introduces the Microsoft machine learning algorithms and models for Python, as related to SQL Server machine learning workloads.
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description: microsoftml is a Python package from Microsoft that provides high-performance machine learning algorithms. It includes functions for training and transformations, scoring, text and image analysis, and feature extraction for deriving values from existing data. The package is included in SQL Server Machine Learning Services.
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ms.prod: sql
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ms.technology: machine-learning-services
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ms.date: 11/06/2019
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ms.date: 07/14/2020
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ms.topic: how-to
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author: dphansen
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ms.author: davidph
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monikerRange: ">=sql-server-2017||>=sql-server-linux-ver15||=sqlallproducts-allversions"
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---
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# microsoftml (Python module in SQL Server)
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# microsoftml (Python package in SQL Server Machine Learning Services)
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[!INCLUDE [SQL Server](../../includes/applies-to-version/sqlserver.md)]
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**microsoftml** is a Python35-compatible module from Microsoft providing high-performance machine learning algorithms. It includes functions for training and transformations, scoring, text and image analysis, and feature extraction for deriving values from existing data.
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The machine learning APIs were developed by Microsoft for internal machine learning applications and have been refined over the years to support high performance on big data, using multicore processing and fast data streaming. This package originated as a Python equivalent of an R version, [MicrosoftML](../r/ref-r-microsoftml.md), that has similar functions.
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**microsoftml** is a Python package from Microsoft that provides high-performance machine learning algorithms. It includes functions for training and transformations, scoring, text and image analysis, and feature extraction for deriving values from existing data. The package is included in [SQL Server Machine Learning Services](../sql-server-machine-learning-services.md) and supports high performance on big data, using multicore processing, and fast data streaming.
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## Full reference documentation
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The **microsoftml** library is distributed in multiple Microsoft products, but usage is the same whether you get the library in SQL Server or another product. Because the functions are the same, [documentation for individual microsoftml functions](https://docs.microsoft.com/machine-learning-server/python-reference/microsoftml/microsoftml-package) is published to just one location under the [Python reference](https://docs.microsoft.com/machine-learning-server/python-reference/introducing-python-package-reference) for Microsoft Machine Learning Server. Should any product-specific behaviors exist, discrepancies will be noted in the function help page.
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The **microsoftml** package is distributed in multiple Microsoft products, but usage is the same whether you get the package in SQL Server or another product. Because the functions are the same, [documentation for individual microsoftml functions](https://docs.microsoft.com/machine-learning-server/python-reference/microsoftml/microsoftml-package) is published to just one location under the [Python reference](https://docs.microsoft.com/machine-learning-server/python-reference/introducing-python-package-reference) for Microsoft Machine Learning Server. Should any product-specific behaviors exist, discrepancies will be noted in the function help page.
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## Versions and platforms
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Algorithms in **microsoftml** depend on [revoscalepy](ref-py-revoscalepy.md) for:
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+ Data source objects. Data consumed by **microsoftml** functions are created using **revoscalepy** functions.
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+ Remote computing (shifting function execution to a remote SQL Server instance). The **revoscalepy** library provides functions for creating and activating a remote compute context for SQL server.
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+ Remote computing (shifting function execution to a remote SQL Server instance). The **revoscalepy** package provides functions for creating and activating a remote compute context for SQL server.
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In most cases, you will load the packages together whenever you are using **microsoftml**.
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docs/machine-learning/python/ref-py-revoscalepy.md

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title: revoscalepy Python package
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description: Introduction to the revoscalepy module in SQL Server Machine Learning Services with Python.
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description: revoscalepy is a Python package from Microsoft that supports distributed computing, remote compute contexts, and high-performance data science algorithms. The package is included in SQL Server Machine Learning Services.
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ms.prod: sql
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ms.technology: machine-learning-services
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ms.date: 11/06/2019
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ms.date: 07/14/2020
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ms.topic: how-to
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author: dphansen
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monikerRange: ">=sql-server-2017||>=sql-server-linux-ver15||=sqlallproducts-allversions"
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---
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# revoscalepy (Python module in SQL Server)
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# revoscalepy (Python package in SQL Server Machine Learning Services)
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[!INCLUDE [SQL Server](../../includes/applies-to-version/sqlserver.md)]
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**revoscalepy** is a Python35-compatible module from Microsoft that supports distributed computing, remote compute contexts, and high-performance data science algorithms. It is based on the **RevoScaleR** package for R (distributed with Microsoft R Server and SQL Server R Services), offering similar functionality:
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**revoscalepy** is a Python package from Microsoft that supports distributed computing, remote compute contexts, and high-performance data science algorithms. The package is included in [SQL Server Machine Learning Services](../sql-server-machine-learning-services.md).
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The package offers the following functionality:
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+ Local and remote compute contexts on systems having the same version of **revoscalepy**
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+ Data transformation and visualization functions
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## Full reference documentation
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The **revoscalepy** library is distributed in multiple Microsoft products, but usage is the same whether you get the library in SQL Server or another product. Because the functions are the same, [documentation for individual revoscalepy functions](https://docs.microsoft.com/machine-learning-server/python-reference/revoscalepy/revoscalepy-package) is published to just one location under the [Python reference](https://docs.microsoft.com/machine-learning-server/python-reference/introducing-python-package-reference) for Microsoft Machine Learning Server. Should any product-specific behaviors exist, discrepancies will be noted in the function help page.
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The **revoscalepy** package is distributed in multiple Microsoft products, but usage is the same whether you get the package in SQL Server or another product. Because the functions are the same, [documentation for individual revoscalepy functions](https://docs.microsoft.com/machine-learning-server/python-reference/revoscalepy/revoscalepy-package) is published to just one location under the [Python reference](https://docs.microsoft.com/machine-learning-server/python-reference/introducing-python-package-reference) for Microsoft Machine Learning Server. Should any product-specific behaviors exist, discrepancies will be noted in the function help page.
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## Versions and platforms
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+ [Python client libraries for a data science client](setup-python-client-tools-sql.md)
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> [!NOTE]
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> Full product release versions are Windows-only in SQL Server 2017. Both Windows and Linux are supported for **revoscalepy** in [SQL Server 2019](../../linux/sql-server-linux-setup-machine-learning.md).
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> Full product release versions are Windows-only in SQL Server 2017. Both Windows and Linux are supported for **revoscalepy** in [SQL Server 2019](../../linux/sql-server-linux-setup-machine-learning.md) and later.
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## Functions by category
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docs/machine-learning/r/ref-r-microsoftml.md

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title: MicrosoftML R function library
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description: Introduction to the MicrosoftML function library in SQL Server 2016 R Services and SQL Server Machine Learning Services with R.
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title: MicrosoftML R package
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description: MicrosoftML is an R package from Microsoft that provides high-performance machine learning algorithms. It includes functions for training and transformations, scoring, text and image analysis, and feature extraction for deriving values from existing data. The package is included in SQL Server Machine Learning Services and SQL Server 2016 R Services and supports high performance on big data, using multicore processing, and fast data streaming. MicrosoftML also includes numerous transformations for text and image processing.
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monikerRange: ">=sql-server-2016||>=sql-server-linux-ver15||=sqlallproducts-allversions"
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---
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# MicrosoftML (R library in SQL Server)
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# MicrosoftML (R package in SQL Server Machine Learning Services)
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[!INCLUDE [SQL Server](../../includes/applies-to-version/sqlserver.md)]
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**MicrosoftML** is an R function library from Microsoft providing high-performance machine learning algorithms. It includes functions for training and transformations, scoring, text and image analysis, and feature extraction for deriving values from existing data.
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The machine learning APIs were developed by Microsoft for internal machine learning applications, and have been refined over the years to support high performance on big data, using multicore processing and fast data streaming. MicrosoftML also includes numerous transformations for text and image processing.
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**MicrosoftML** is an R package from Microsoft that provides high-performance machine learning algorithms. It includes functions for training and transformations, scoring, text and image analysis, and feature extraction for deriving values from existing data. The package is included in [SQL Server Machine Learning Services](../sql-server-machine-learning-services.md) and [SQL Server 2016 R Services](sql-server-r-services.md) and supports high performance on big data, using multicore processing, and fast data streaming. MicrosoftML also includes numerous transformations for text and image processing.
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## Full reference documentation
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The **MicrosoftML** library is distributed in multiple Microsoft products, but usage is the same whether you get the library in SQL Server or another product. Because the functions are the same, [documentation for individual RevoScaleR functions](https://docs.microsoft.com/machine-learning-server/r-reference/revoscaler/revoscaler) is published to just one location under the [R reference](https://docs.microsoft.com/machine-learning-server/r-reference/introducing-r-server-r-package-reference) for Microsoft Machine Learning Server. Should any product-specific behaviors exist, discrepancies will be noted in the function help page.
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The **MicrosoftML** package is distributed in multiple Microsoft products, but usage is the same whether you get the package in SQL Server or another product. Because the functions are the same, [documentation for individual RevoScaleR functions](https://docs.microsoft.com/machine-learning-server/r-reference/revoscaler/revoscaler) is published to just one location under the [R reference](https://docs.microsoft.com/machine-learning-server/r-reference/introducing-r-server-r-package-reference) for Microsoft Machine Learning Server. Should any product-specific behaviors exist, discrepancies will be noted in the function help page.
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## Versions and platforms
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The **MicrosoftML** library is based on R 3.4.3 and available only when you install one of the following Microsoft products or downloads:
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The **MicrosoftML** package is based on R 3.4.3 and available only when you install one of the following Microsoft products or downloads:
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+ [SQL Server 2016 R Services](../install/sql-r-services-windows-install.md)
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+ [SQL Server Machine Learning Services](../install/sql-machine-learning-services-windows-install.md)
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Algorithms in **MicrosoftML** depend on [RevoScaleR](ref-r-revoscaler.md) for:
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+ Data source objects. Data consumed by **MicrosoftML** functions are created using **RevoScaleR** functions.
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+ Remote computing (shifting function execution to a remote SQL Server instance). The **RevoScaleR** library provides functions for creating and activating a remote compute context for SQL server.
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+ Remote computing (shifting function execution to a remote SQL Server instance). The **RevoScaleR** package provides functions for creating and activating a remote compute context for SQL server.
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In most cases, you will load the packages together whenever you are using **MicrosoftML**.
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docs/machine-learning/r/ref-r-olapr.md

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title: olapR R function library
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description: Introduction to the olapR function library in SQL Server 2016 R Services and SQL Server Machine Learning Services with R.
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title: olapR R package
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description: olapR is an R package from Microsoft used for MDX queries against a SQL Server Analysis Services OLAP cube. Functions do not support all MDX operations, but you can build queries that slice, dice, drilldown, rollup, and pivot on dimensions. The package is included in SQL Server Machine Learning Services and SQL Server 2016 R Services.
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ms.date: 12/04/2018
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# olapR (R library in SQL Server)
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# olapR (R package in SQL Server Machine Learning Services)
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[!INCLUDE [SQL Server](../../includes/applies-to-version/sqlserver.md)]
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**olapR** is a Microsoft library of R functions used for MDX queries against a SQL Server Analysis Services OLAP cube. Functions do not support all MDX operations, but you can build queries that slice, dice, drilldown, rollup, and pivot on dimensions.
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**olapR** is an R package from Microsoft used for MDX queries against a SQL Server Analysis Services OLAP cube. Functions do not support all MDX operations, but you can build queries that slice, dice, drilldown, rollup, and pivot on dimensions. The package is included in [SQL Server Machine Learning Services](../sql-server-machine-learning-services.md) and [SQL Server 2016 R Services](sql-server-r-services.md).
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You can use this package on connections to an Analysis Services OLAP cube on all supported versions of SQL Server. Connections to a tabular model are not supported at this time.
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This package is not preloaded into an R session. Run the following command to load the library.
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## Load package
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The **olapR** package is not preloaded into an R session. Run the following command to load the package.
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```R
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You can use this library on connections to an Analysis Services OLAP cube on all supported versions of SQL Server. Connections to a tabular model are not supported at this time.
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Current version is 1.0.0 in all Windows-only products and downloads providing the library.
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Current version is 1.0.0 in all Windows-only products and downloads providing the package.
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## Full reference documentation
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The **olapr** library is distributed in multiple Microsoft products, but usage is the same whether you get the library in SQL Server or another product. Because the functions are the same, [documentation for individual sqlrutils functions](https://docs.microsoft.com/machine-learning-server/r-reference/olapr/olapr) is published to just one location under the [R reference](https://docs.microsoft.com/machine-learning-server/r-reference/introducing-r-server-r-package-reference) for Microsoft Machine Learning Server. Should any product-specific behaviors exist, discrepancies will be noted in the function help page.
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The **olapr** package is distributed in multiple Microsoft products, but usage is the same whether you get the package in SQL Server or another product. Because the functions are the same, [documentation for individual sqlrutils functions](https://docs.microsoft.com/machine-learning-server/r-reference/olapr/olapr) is published to just one location under the [R reference](https://docs.microsoft.com/machine-learning-server/r-reference/introducing-r-server-r-package-reference) for Microsoft Machine Learning Server. Should any product-specific behaviors exist, discrepancies will be noted in the function help page.
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## Availability and location
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Data Science Virtual Machine (on Azure) | C:\Program Files\Microsoft\R Client\R_SERVER\library |
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SQL Server Virtual Machine (on Azure) <sup>1</sup> | C:\Program Files\Microsoft SQL Server\MSSQL14.MSSQLSERVER\R_SERVICES\library |
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<sup>1</sup> R integration is optional in SQL Server. The olapR library will be installed when you add the Machine Learning or R feature during VM configuration.
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<sup>1</sup> R integration is optional in SQL Server. The olapR package will be installed when you add the Machine Learning or R feature during VM configuration.
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## See also

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