Merge pull request #7153 from HeidiSteen/heidist-ctp2

LP and TOC changes per PM review

Author: GitHubber17

docs/advanced-analytics/index.md

@@ -1,5 +1,6 @@
 ---
-title: SQL Server programming extensions product documentation | Microsoft Docs
+title: SQL Server machine learning and programming extensions documentation | Microsoft Docs
+description: R and Python in SQL Server, with built-in data science modeling and machine learning algorithms for enterprise data analysis at scale.
 ms.prod: sql
 ms.technology: machine-learning
 
@@ -11,18 +12,30 @@ manager: cgronlun
 monikerRange: ">=sql-server-2016||=sqlallproducts-allversions"
 ---
 
-# SQL Server Programming Extensions Documentation
+::: moniker range="=sql-server-ver15||=sqlallproducts-allversions"
+# SQL Server Machine Learning and Programming Extensions Documentation
 
-Learn how to use external libraries and languages on resident, relational data with our quickstarts, tutorials, and how-to articles. 
-R and Python libraries in [SQL Server machine learning](what-is-sql-server-machine-learning.md) include base distributions, machine learning algorithms, and functions for conducting high-performance analytics at scale, without having to transfer data across the network. 
+Learn how to use R and Python external libraries and languages on resident, relational data with our quickstarts, tutorials, and how-to articles. R and Python libraries in [SQL Server machine learning](what-is-sql-server-machine-learning.md) include base distributions, data science models, machine learning algorithms, and functions for conducting high-performance analytics at scale, without having to transfer data across the network. 
 
-Java code execution uses the same extensibility framework as R and Python, but does not include data science and machine learning function libraries.
+In SQL Server 2019, Java code execution uses the same extensibility framework as R and Python, but does not include data science and machine learning function libraries.
 
 |   |   | 
 |---|---|-
 | ![R logo](./media/index/logo_r.png) | Open-source R, extended with [RevoScaleR](https://docs.microsoft.com/machine-learning-server/r-reference/revoscaler/revoscaler) and Microsoft AI algorithms in [MicrosoftML](https://docs.microsoft.com/machine-learning-server/r-reference/microsoftml/microsoftml-package). These libraries give you forecasting and prediction models, statistical analysis, visualization, and data manipulation at scale. <br/>R integration starts in [SQL Server 2016](./install/sql-r-services-windows-install.md) and is also in [SQL Server 2017](./install/sql-machine-learning-services-windows-install.md). | 
 | ![Python logo](./media/index/logo_python.png) | Python developers can use Microsoft [revoscalepy](https://docs.microsoft.com/machine-learning-server/python-reference/revoscalepy/revoscalepy-package) and [microsoftml](https://docs.microsoft.com/machine-learning-server/python-reference/microsoftml/microsoftml-package) libraries for predictive analytics and machine learning at scale. Anaconda and Python 3.5-compatible libraries are the baseline distribution. <br/>Python integration starts in [SQL Server 2017](./install/sql-machine-learning-services-windows-install.md).  | 
-| ![Java logo](./media/index/logo_java.png) | Java developers can use the [Java language extension](java/extension-java.md) to wrap code in stored procedures or in a binary format accessible through Transact-SQL. <br/>Java integration is currently [SQL Server 2019 only](./install/sql-machine-learning-services-ver15.md). |
+| ![Java logo](./media/index/logo_java.png) | Java developers can use the [Java language extension](java/extension-java.md) to wrap code in stored procedures or in a binary format accessible through Transact-SQL. <br/>Java integration starts in [SQL Server 2019 - preview](./install/sql-machine-learning-services-ver15.md). |
+::: moniker-end
+
+::: moniker range="=sql-server-2016||=sql-server-2017"
+# SQL Server Machine Learning R and Python Documentation
+
+Learn how to use R and Python external libraries and languages on resident, relational data with our quickstarts, tutorials, and how-to articles. R and Python libraries in [SQL Server machine learning](what-is-sql-server-machine-learning.md) include base distributions, data science models, machine learning algorithms, and functions for conducting high-performance analytics at scale, without having to transfer data across the network. 
+
+|   |   | 
+|---|---|-
+| ![R logo](./media/index/logo_r.png) | Open-source R, extended with [RevoScaleR](https://docs.microsoft.com/machine-learning-server/r-reference/revoscaler/revoscaler) and Microsoft AI algorithms in [MicrosoftML](https://docs.microsoft.com/machine-learning-server/r-reference/microsoftml/microsoftml-package). These libraries give you forecasting and prediction models, statistical analysis, visualization, and data manipulation at scale. <br/>R integration starts in [SQL Server 2016](./install/sql-r-services-windows-install.md) and is also in [SQL Server 2017](./install/sql-machine-learning-services-windows-install.md). | 
+| ![Python logo](./media/index/logo_python.png) | Python developers can use Microsoft [revoscalepy](https://docs.microsoft.com/machine-learning-server/python-reference/revoscalepy/revoscalepy-package) and [microsoftml](https://docs.microsoft.com/machine-learning-server/python-reference/microsoftml/microsoftml-package) libraries for predictive analytics and machine learning at scale. Anaconda and Python 3.5-compatible libraries are the baseline distribution. <br/>Python integration starts in [SQL Server 2017](./install/sql-machine-learning-services-windows-install.md).  | 
+::: moniker-end
 
 ## 5-Minute Quickstarts
 

docs/advanced-analytics/java/extension-java.md

@@ -22,7 +22,7 @@ To use the Java extension to run your own code, follow these steps.
 
 Run SQL Server 2019 Setup on Windows or Linux to install a database engine instance, adding the Machine Learning Services feature. This feature provides the extensibility framework and adds the security layer that isolates code execution, and protects data from unauthorized access.
 
-+ On Windows, start the [Installation Wziard](../install/sql-machine-learning-services-windows-install.md). In Feature Selection, select **Machine Learning Services (in-database)**. You can omit R and Python if you wish.
++ On Windows, start the [Installation Wizard](../install/sql-machine-learning-services-windows-install.md). In Feature Selection, select **Machine Learning Services (in-database)**. You can omit R and Python if you wish.
 
 + On Linux, install the [database engine and extensibility package](../../linux/sql-server-linux-setup-machine-learning.md).