Learn Editor: Update how-to-interactive-jobs.md

Author: joburges

articles/machine-learning/how-to-interactive-jobs.md

@@ -31,7 +31,7 @@ Interactive training is supported on **Azure Machine Learning Compute Clusters**
 - To use **VS Code**, [follow this guide](how-to-setup-vs-code.md) to set up the Azure Machine Learning extension.
 - Make sure your job environment has the `openssh-server` and `ipykernel ~=6.0` packages installed (all Azure Machine Learning curated training environments have these packages installed by default).
 - Interactive applications can't be enabled on distributed training runs where the distribution type is anything other than Pytorch, Tensorflow or MPI. Custom distributed training setup (configuring multi-node training without using the above distribution frameworks) is not currently supported.
-- To use SSH, you will need an SSH key pair. You can use the `ssh-keygen -f "<filepath>"` command to generate a public and private key pair.
+- To use SSH, you need an SSH key pair. You can use the `ssh-keygen -f "<filepath>"` command to generate a public and private key pair.
 
 ## Interact with your job container
 
@@ -182,6 +182,12 @@ To interact with your running job, click the button **Debug and monitor** on the
 
 
 
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 Clicking the applications in the panel opens a new tab for the applications. You can access the applications only when they are in **Running** status and only the **job owner** is authorized to access the applications. If you're training on multiple nodes, you can pick the specific node you would like to interact with.
 
 :::image type="content" source="media/interactive-jobs/interactive-jobs-application-list.png" alt-text="Screenshot of interactive jobs right panel information. Information content will vary depending on the user's data.":::