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docs/machine-learning/install/sql-pretrained-models-install.md

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@@ -35,15 +35,15 @@ You must have administrator rights on the computer and SQL Server to add pre-tra
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External scripts must be enabled and SQL Server LaunchPad service must be running. Installation instructions provide the steps for enabling and verifying these capabilities.
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::: moniker range=">=sql-server-2017"
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[MicrosoftML R package](../r/reference/microsoftml/microsoftml-package.md) or [microsoftml Python package](../python/ref-py-microsoftml.md) contain the pre-trained models.
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[MicrosoftML R package](../r/ref-r-microsoftml.md) or [microsoftml Python package](../python/ref-py-microsoftml.md) contain the pre-trained models.
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[SQL Server Machine Learning Services](sql-machine-learning-services-windows-install.md) includes both language versions of the machine learning library, so this prerequisite is met with no further action on your part. Because the libraries are present, you can use the PowerShell script described in this article to add the pre-trained models to these libraries.
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::: moniker-end
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::: moniker range="=sql-server-2016"
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[MicrosoftML R package](../r/reference/microsoftml/microsoftml-package.md) contain the pre-trained models.
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[MicrosoftML R package](../r/ref-r-microsoftml.md) contain the pre-trained models.
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[SQL Server R Services](sql-r-services-windows-install.md), which is R only, does not include [MicrosoftML package](../r/reference/microsoftml/microsoftml-package.md) out of the box. To add MicrosoftML, you must do a [component upgrade](../install/upgrade-r-and-python.md). One advantage of the component upgrade is that you can simultaneously add the pre-trained models, which makes running the PowerShell script unnecessary. However, if you already upgraded but missed adding the pre-trained models the first time around, you can run the PowerShell script as described in this article. It works for both versions of SQL Server. Before you do, confirm that the MicrosoftML library exists at `C:\Program Files\Microsoft SQL Server\MSSQL13.MSSQLSERVER\R_SERVICES\library`.
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[SQL Server R Services](sql-r-services-windows-install.md), which is R only, does not include [MicrosoftML package](../r/ref-r-microsoftml.md) out of the box. To add MicrosoftML, you must do a [component upgrade](../install/upgrade-r-and-python.md). One advantage of the component upgrade is that you can simultaneously add the pre-trained models, which makes running the PowerShell script unnecessary. However, if you already upgraded but missed adding the pre-trained models the first time around, you can run the PowerShell script as described in this article. It works for both versions of SQL Server. Before you do, confirm that the MicrosoftML library exists at `C:\Program Files\Microsoft SQL Server\MSSQL13.MSSQLSERVER\R_SERVICES\library`.
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::: moniker-end
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<a name="file-location"></a>
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+ [SQL Server Machine Learning Services](sql-machine-learning-services-windows-install.md)
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+ [Upgrade R and Python components in SQL Server instances](../install/upgrade-r-and-python.md)
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+ [MicrosoftML package for R](../r/reference/microsoftml/microsoftml-package.md)
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+ [MicrosoftML package for R](../r/ref-r-microsoftml.md)
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+ [microsoftml package for Python](../python/ref-py-microsoftml.md)

docs/machine-learning/install/upgrade-r-and-python.md

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For SQL Server 2016 R Services customers, binding provides:
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- Updated R packages.
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- New packages not part of the original installation ([MicrosoftML](../r/reference/microsoftml/microsoftml-package.md))
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- New packages not part of the original installation ([MicrosoftML](../r/ref-r-microsoftml.md))
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- Pre-trained machine learning [models](/machine-learning-server/install/microsoftml-install-pretrained-models) for sentiment analysis and image detection.
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All of the binding can further be refreshed at each new major and minor release of [Microsoft Machine Learning Server](/machine-learning-server/index).
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----------|----------------|----------------|--------------|---------|-------|-------|
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Microsoft R Open (MRO) over R | R 3.2.2 | R 3.3.2 |R 3.3.3 | R 3.4.1 | R 3.4.3 | R 3.5.2
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[RevoScaleR](/machine-learning-server/r-reference/revoscaler/revoscaler) | 8.0.3 | 9.0.1 | 9.1 | 9.2.1 | 9.3 | 9.4.7 |
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[MicrosoftML](../r/reference/microsoftml/microsoftml-package.md)| n.a. | 9.0.1 | 9.1 | 9.2.1 | 9.3 | 9.4.7 |
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[MicrosoftML](../r/ref-r-microsoftml.md)| n.a. | 9.0.1 | 9.1 | 9.2.1 | 9.3 | 9.4.7 |
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[pretrained models](/machine-learning-server/install/microsoftml-install-pretrained-models)| n.a. | 9.0.1 | 9.1 | 9.2.1 | 9.3 | 9.4.7 |
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[sqlrutils](../r/reference/sqlrutils/sqlrutils.md)| n.a. | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
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[olapR](../r/reference/olapr/olapr.md) | n.a. | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
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Microsoft R Open (MRO) over R | R 3.3.3 | R 3.4.3 | R 3.5.2 |
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[RevoScaleR](/machine-learning-server/r-reference/revoscaler/revoscaler) | 9.2 | 9.3 | 9.4.7 |
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[MicrosoftML](../r/reference/microsoftml/microsoftml-package.md) | 9.2 | 9.3| 9.4.7 |
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[MicrosoftML](../r/ref-r-microsoftml.md) | 9.2 | 9.3| 9.4.7 |
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[sqlrutils](../r/reference/sqlrutils/sqlrutils.md)| 1.0 | 1.0 | 1.0 |
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[olapR](../r/reference/olapr/olapr.md) | 1.0 | 1.0 | 1.0 |
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Anaconda 4.2 over Python 3.5 | 4.2/3.5.2 | 4.2/3.5.2 |

docs/machine-learning/r/reference/olapr/olapr.md

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docs/machine-learning/r/reference/sqlrutils/setinputparametervalue.md

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