Merge pull request #272977 from fbsolo-ms1/update-data-science-virtual-machine-files

Freshness update for dsvm-tools-languages.md . . .

Author: v-dirichards

articles/machine-learning/data-science-virtual-machine/dsvm-tools-data-science.md

@@ -10,6 +10,7 @@ ms.custom: devx-track-python
 author: timoklimmer
 ms.author: tklimmer
 ms.topic: conceptual
+ms.reviewer: franksolomon
 ms.date: 04/17/2024
 ---
 

articles/machine-learning/data-science-virtual-machine/dsvm-tools-ingestion.md

@@ -10,6 +10,7 @@ ms.custom: devx-track-azurecli
 author: timoklimmer
 ms.author: tklimmer
 ms.topic: conceptual
+ms.reviewer: franksolomon
 ms.date: 04/19/2024
 ---
 
@@ -41,7 +42,7 @@ The DSVM offers these data movement tools:
 
 ## Azure Cosmos DB Data Migration tool
 
-|--|--|
+| Category | Value |
 | ------------- | ------------- |
 | What is it? | Tool to import data from various sources into Azure Cosmos DB, a NoSQL database in the cloud. These sources include JSON files<br>CSV files<br>SQL<br>MongoDB<br>Azure Table storage<br>Amazon DynamoDB<br>Azure Cosmos DB for NoSQL collections |
 | Supported DSVM versions | Windows |

articles/machine-learning/data-science-virtual-machine/dsvm-tools-languages.md

@@ -1,7 +1,7 @@
 ---
 title: Supported languages
 titleSuffix: Azure Data Science Virtual Machine 
-description: The supported program languages and related tools pre-installed on the Data Science Virtual Machine.
+description: The supported program languages and related tools preinstalled on the Data Science Virtual Machine.
 keywords: data science tools, data science virtual machine, tools for data science, linux data science
 services: machine-learning
 ms.service: data-science-vm
@@ -10,29 +10,28 @@ ms.custom: devx-track-python
 author: jesscioffi
 ms.author: jcioffi
 ms.topic: conceptual
-ms.date: 06/23/2022
-
+ms.reviewer: franksolomon
+ms.date: 04/22/2024
 
 ---
 
-# Languages supported on the Data Science Virtual Machine 
+# Languages supported on the Data Science Virtual Machine
 
-The Data Science Virtual Machine (DSVM) comes with several pre-built languages and development tools for building your
-artificial intelligence (AI) applications. Here are some of the notable ones.
+To build artificial intelligence (AI) applications, the Data Science Virtual Machine (DSVM) includes with several prebuilt languages and development tools:
 
 ## Python
 
 | Category | Value |
 |--|--|
 | Language versions supported | Python 3.8 |
 | Supported DSVM editions | Windows Server 2019, Linux |
-| How is it configured / installed on the DSVM? | There is multiple `conda` environments whereby each of these has different Python packages pre-installed. To list all available environments in your machine, run `conda env list`. |
+| How is it configured and installed on the DSVM? | Multiple `conda` environments include different, preinstalled Python packages. Run `conda env list` to list all available environments in your machine. |
 
 ### How to use and run it
 
-* Run at a command prompt:
+* At a command prompt:
 
-  Open a command prompt and use one of the following methods, depending on the version of Python you want to run:
+  Use one of these methods, depending on the version of Python you want to run:
 
     ```
     conda activate <conda_environment_name>
@@ -41,24 +40,19 @@ artificial intelligence (AI) applications. Here are some of the notable ones.
     
 * Use in an IDE:
 
-  The DSVM images have several IDEs installed such as VS.Code or PyCharm. You can use them to edit, run and debug your
-  Python scripts.
+  The DSVM images have several IDEs installed - for example, VS.Code or PyCharm. You can use them to edit, run, and debug your Python scripts.
 
 * Use in Jupyter Lab:
 
-  Open a Launcher tab in Jupyter Lab and select the type and kernel of your new document. If you want your document to be
-  placed in a certain folder, navigate to that folder in the File Browser on the left side first.
+  Open a Launcher tab in Jupyter Lab, and select the type and kernel of your new document. To place your document in a specific folder, first navigate to that folder in the File Browser on the left side.
 
 * Install Python packages:
 
-  To install a new package, you need to activate the right environment first. The environment is the place where your
-  new package will be installed, and the package will then only be available in that environment.
+  To install a new package, you must first activate the proper environment. The proper environment is the location where your new package will be installed. The package will then only become available in that environment.
 
-  To activate an environment, run `conda activate <environment_name>`. Once the environment is activated, you can use
-  a package manager like `conda` or `pip` to install or update a package.
+  To activate an environment, run `conda activate <environment_name>`. Once the environment is activated, you can use a package manager -for example, `conda` or `pip` - to install or update a package.
 
-  As an alternative, if you are using Jupyter, you can also install packages directly by running
-`!pip install --upgrade <package_name>` in a cell.
+  As an alternative, if you use Jupyter, you can also run `!pip install --upgrade <package_name>` in a cell to install packages directly.
 
 ## R
 
@@ -75,12 +69,11 @@ artificial intelligence (AI) applications. Here are some of the notable ones.
 
 * Use in Jupyter Lab
 
-  Open a Launcher tab in Jupyter Lab and select the type and kernel of your new document. If you want your document to be
-  placed in a certain folder, navigate to that folder in the File Browser on the left side first.
+  Open a Launcher tab in Jupyter Lab, and select the type and kernel of your new document. To place your document in a specific folder, first navigate to that folder in the File Browser on the left side.
 
 * Install R packages:
 
-  You can install new R packages by using the `install.packages()` function.
+  You can install new R packages with the `install.packages()` function.
 
 ## Julia
 
@@ -89,7 +82,6 @@ artificial intelligence (AI) applications. Here are some of the notable ones.
 | Language versions supported | 1.0.5 |
 | Supported DSVM editions      | Linux, Windows     |
 
-
 ### How to use and run it    
 
 * Run at a command prompt
@@ -98,20 +90,18 @@ artificial intelligence (AI) applications. Here are some of the notable ones.
 
 * Use in Jupyter:
 
-  Open a Launcher tab in Jupyter and select the type and kernel of your new document. If you want your document to be
-  placed in a certain folder, navigate to that folder in the File Browser on the left side first.
+  Open a Launcher tab in Jupyter Lab, and select the type and kernel of your new document. To place your document in a specific folder, first navigate to that folder in the File Browser on the left side.
 
 * Install Julia packages:
 
-  You can use Julia package manager commands like `Pkg.add()` to install or update packages.
-
+  You can install or update packages with Julia package manager commands like `Pkg.add()`.
 
 ## Other languages
 
-**C#**: Available on Windows and accessible through the Visual Studio Community edition or at the `Developer Command Prompt for Visual Studio`, where you can run the `csc` command.
+**C#**: Available on Windows and accessible through the Visual Studio Community edition. You can also run the `csc` command at the `Developer Command Prompt for Visual Studio`.
 
-**Java**: OpenJDK is available on both the Linux and Windows editions of the DSVM and is set on the path. To use Java, type the `javac` or `java` command at a command prompt in Windows or on the bash shell in Linux.
+**Java**: OpenJDK is available on both the Linux and Windows DSVM editions. It's set on the path. To use Java, type the `javac` or `java` command at a command prompt in Windows, or on the bash shell in Linux.
 
-**Node.js**: Node.js is available on both the Linux and Windows editions of the DSVM and is set on the path. To access Node.js, type the `node` or `npm` command at a command prompt in Windows or on the bash shell in Linux. On Windows, the Visual Studio extension for the Node.js tools is installed to provide a graphical IDE to develop your Node.js application.
+**Node.js**: Node.js is available on both the Linux and Windows editions of the DSVM. It's set on the path. To access Node.js, type the `node` or `npm` command at a Windows command prompt or in a Linux Bash shell. On Windows, the Visual Studio extension for the Node.js tools is installed. It provides a graphical IDE for Node.js application development.
 
-**F#**: Available on Windows and accessible through the Visual Studio Community edition or at a `Developer Command Prompt for Visual Studio`, where you can run the `fsc` command.
+**F#**: Available on Windows and accessible through the Visual Studio Community edition or at a `Developer Command Prompt for Visual Studio`, where you can run the `fsc` command.