Merge pull request #2176 from HeidiSteen/heidist-master

fixing links and link text

Author: PRMerger7

docs/advanced-analytics/getting-started-with-machine-learning-services.md

@@ -48,7 +48,7 @@ The option to install Microsoft R Server is provided in SQL Server 2016 to suppo
 
 You can also install R Server through platform-specific installers available from MSDN:
 
-  + [R Server for Windows](https://msdn.microsoft.commicrosoft-r/rserver-install-windows)
+  + [R Server for Windows](https://msdn.microsoft.com/microsoft-r/rserver-install-windows)
   + [R Server for Linux](https://msdn.microsoft.com/microsoft-r/rserver-install-linux-server)
   + [R Server for Hadoop](https://msdn.microsoft.com/microsoft-r/rserver-install-hadoop)
 

docs/advanced-analytics/r/data-exploration-and-predictive-modeling-with-r.md

@@ -37,7 +37,7 @@ The new, scalable packages and R functions included with [!INCLUDE[rsql_productn
 
 ## What's Different about RevoScaleR?
 
-The **RevoScaleR** package contains implementations of some of the most popular R functions, which have been redesigned to provide parallelism and scale. For more information, see [Distributed Computing using RevoScaleR](https://msdn.microsoft.com/microsoft-r/scaler-distributed-computing)...
+The **RevoScaleR** package contains implementations of some of the most popular R functions, which have been redesigned to provide parallelism and scale. For more information, see [Distributed Computing using RevoScaleR](https://msdn.microsoft.com/microsoft-r/scaler-distributed-computing).
 
 The RevoScaleR package also provides support for changing *execution context*. What this means is that, for an entire solution or for just one function, you can indicate that computations should be performed using the resources of the computer that hosts the [!INCLUDE[ssNoVersion](../../includes/ssnoversion-md.md)] instance, rather than your local workstation. There are multiple advantages to doing this: you avoid unnecessary data movement, and you can leverage greater computation resources on the server computer.
 
@@ -61,7 +61,7 @@ In addition to the proprietary R libraries included with Microsoft Machine Learn
 
      The **RevoPemaR** package lets you develop your own parallel external memory algorithms in R.  
 
-     For more information about these packages and how to use them, see Get started with ScaleR and data analysis](https://msdn.microsoft.com/microsoft-r/scaler-getting-started).  
+     For more information about these packages and how to use them, see [What is RevoScaleR](https://msdn.microsoft.com/microsoft-r/scaler-user-guide-introduction) and [Get started with RevoPemaR](https://msdn.microsoft.com/microsoft-r/pemar-getting-started). 
 
 + **MicrosoftML** contains a collection of highly optimized machine learning algorithms and data transformations from the Microsoft Data Science team. Many of the algorithms are also used in Azure Machine Learning. For more information, see [Using the MicrosoftML Package](../../advanced-analytics/using-the-microsoftml-package.md).
 

docs/advanced-analytics/r/r-libraries-and-data-types.md

@@ -34,9 +34,7 @@ To view the R version associated with a particular instance of SQL Server, open
 1. For the default instance, the path would be as follows: `C:\Program Files\Microsoft SQL Server\MSSQL14.MSSQLSERVER\R_SERVICES\bin\x64\`
 2. A message is displayed that lists the R distribution and the Microsoft R Open version number.
 
-To find the version of R included in a particular version of Microsoft R Server, see the [R Server Release Notes](https://msdn.microsoft.com/microsoft-r/notes/r-server-notes).
-
-Additional information about recent releases can be found in the [R Server - What’s New](https://msdn.microsoft.com/microsoft-r/rserver-whats-new) notes.
+To find the version of R included in a particular version of Microsoft R Server, see [R Server - What’s New](https://msdn.microsoft.com/microsoft-r/rserver-whats-new#new-and-updated-packages).
 
 Note that the package management system in SQL Server means that multiple versions of an R package can be installed on the same computer, with multiple users sharing the same package, or using different versions of the same package. For more information, see [R Package Management in SQL Server](../r/r-package-management-for-sql-server-r-services.md).
 

docs/advanced-analytics/r/scaler-functions-for-working-with-sql-server-data.md

@@ -57,7 +57,7 @@ After you have created a data source object, you can open it to get data, or wri
 + [rxWriteNext](https://msdn.microsoft.com/microsoft-r/scaler/packagehelp/rxopen-methods) - Write data to the target
 + [rxClose](https://msdn.microsoft.com/microsoft-r/scaler/packagehelp/rxopen-methods) - Close a data source
 
-For more information about working with these functions, including using data sources other than [!INCLUDE[ssNoVersion_md](../../includes/ssnoversion-md.md)], see [Getting Started with Microsoft R](https://msdn.microsoft.com/microsoft-r/microsoft-r-get-started-node).
+For more information about working with these functions, including using data sources other than [!INCLUDE[ssNoVersion_md](../../includes/ssnoversion-md.md)], see [Tutorial: Data import and exploration](https://msdn.microsoft.com/microsoft-r/scaler-getting-started-data-import-exploration).
 
 ## Work with XDF Files
 

docs/advanced-analytics/tutorials/deepdive-create-new-sql-server-table-using-rxdatastep.md

@@ -65,7 +65,7 @@ After doing some lightweight transformations on the data using the XDF file, you
 
 > [!NOTE]
 > 
-> Did you notice that you did not need to call any other functions to load the data into the XDF file, and could call rxGetVarInfo on the data immediately? That's because XDF is the default interim storage method for RevoScaleR. For more information about XDF files, see the [ScaleR Getting Started Guide](https://msdn.microsoft.com/microsoft-r/scaler-user-guide-data-transform#using-the-data-step-to-create-an-xdf-file-from-a-data-frame)
+> Did you notice that you did not need to call any other functions to load the data into the XDF file, and could call rxGetVarInfo on the data immediately? That's because XDF is the default interim storage method for RevoScaleR. For more information about XDF files, see [Create an XDF](https://msdn.microsoft.com/microsoft-r/scaler-data-xdf).
 
 4. Now, you'll put this data into a [!INCLUDE[ssNoVersion](../../includes/ssnoversion-md.md)] table, storing _DayOfWeek_ as an integer with values from 1 to 7.
   

docs/advanced-analytics/tutorials/deepdive-data-science-deep-dive-using-the-revoscaler-packages.md

@@ -29,9 +29,9 @@ You will learn how to create a remote compute context, move data between local a
 > 
 > This tutorial works specifically with SQL Server data on Windows, and uses in-database compute contexts. If you want to use R in other contexts, such as Teradata, Linux, or Hadoop, see these Microsoft R Server tutorials: 
 > + [Use R Server with sparklyr](https://msdn.microsoft.com/microsoft-r/microsoft-r-get-started-spark-interop)
-> + [Explore R and ScaleR in 25 functions](https://msdn.microsoft.com/microsoft-r/microsoft-r-getting-started-tutorial)
+> + [Explore R and ScaleR in 25 functions](https://msdn.microsoft.com/microsoft-r/microsoft-r-tutorial-r2revoscaler)
 > + [Get Started with ScaleR on Hadoop MapReduce](https://msdn.microsoft.com/microsoft-r/scaler-hadoop-getting-started)
-> [RevoScaleR Teradata Getting Started Guide](https://msdn.microsoft.com/microsoft-r/scaler-teradata-getting-started)
+> + [RevoScaleR Teradata Getting Started Guide](https://msdn.microsoft.com/microsoft-r/scaler-teradata-getting-started)
 
 ## Overview
 

docs/advanced-analytics/tutorials/rtsql-predict-and-plot-from-model.md

@@ -175,7 +175,7 @@ To continue learning about solutions using R with SQL Server, see the tutorials
 
 For guidance on using the new RevoScaleR packages, see these resources for [Microsoft R](https://msdn.microsoft.com/microsoft-r/microsoft-r-getting-started):
 
-+ [Explore R and ScaleR in 25 functions](https://msdn.microsoft.com/microsoft-r/microsoft-r-getting-started-tutorial)
++ [Explore R and ScaleR in 25 functions](https://msdn.microsoft.com/microsoft-r/microsoft-r-tutorial-r2revoscaler)
 + [Fitting Linear Models](https://msdn.microsoft.com/microsoft-r/scaler-user-guide-linear-model)
 + [Models in RevoScaleR](https://msdn.microsoft.com/microsoft-r/scaler-user-guide-models)
 

docs/advanced-analytics/tutorials/walkthrough-deploy-and-use-the-model.md

@@ -217,6 +217,7 @@ We also recommend that you check out some of these additional samples and resour
 + [In-database advanced analytics](../../advanced-analytics/r-services/in-database-advanced-analytics-for-sql-developers-tutorial.md)
 + [Microsoft R - Diving into Data Analysis](https://msdn.microsoft.com/microsoft-r/data-analysis-in-microsoft-r)
 + [Additional Resources](https://msdn.microsoft.com/microsoft-r/microsoft-r-more-resources)
+
 ## Previous Lesson  
 [Lesson 4: Build and Save the Model (Data Science End-to-End Walkthrough)](../../advanced-analytics/r-services/lesson-4-build-and-save-the-model-data-science-end-to-end-walkthrough.md)  
   

docs/advanced-analytics/tutorials/walkthrough-prepare-the-data.md

@@ -62,8 +62,7 @@ All the code that you will has been provided in a GitHub repository. You can use
   
     ![After completion of PowerShell script](media/rsql-e2e-psscriptresults.PNG "After completion of PowerShell script")  
   
-5.  In the PowerShell console, you can run the command `ls` to view a list of the files that were downloaded to *DestDir*.  For a description of the filesls
-, see [What's Included](#What-the-Download-Includes).
+5.  In the PowerShell console, you can run the command `ls` to view a list of the files that were downloaded to *DestDir*.  For a description of the files, see [What's Included](#What-the-Download-Includes).
   
 ## 2. Install Required Packages  
 This walkthrough requires some R libraries that are not installed by default as part of [!INCLUDE[rsql_productname](../../includes/rsql-productname-md.md)]. You must install the packages both on the client where you will be developing the solution, and on the [!INCLUDE[ssNoVersion](../../includes/ssnoversion-md.md)] computer where you will deploy the solution.