Update how-to-interactive-jobs.md

Author: ssalgadodev

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

@@ -11,7 +11,7 @@ ms.subservice: automl
 ms.topic: how-to
 ms.custom: devplatv2, sdkv2, cliv2
 
-ms.date: 07/15/2023
+ms.date: 08/15/2024
 #Customer intent: I'm a data scientist with ML knowledge in the machine learning space, looking to build ML models using data in Azure Machine Learning with full control of the model training including debugging and monitoring of live jobs.
 ---
 
@@ -26,7 +26,7 @@ Interactive training is supported on **Azure Machine Learning Compute Clusters**
 - Review [getting started with training on Azure Machine Learning](./how-to-train-model.md).
 - For more information, see this link for [VS Code](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) isn't currently supported.
+- 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) isn't currently supported.
 - 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
@@ -258,7 +258,7 @@ To submit a job with a debugger attached and the execution paused, you can use d
 > [!NOTE]
 > Private link-enabled workspaces are not currently supported when attaching a debugger to a job in VS Code.
 
-1. During job submission (either through the UI, the CLI or the SDK) use the debugpy command to run your python script. For example, the below screenshot shows a sample command that uses debugpy to attach the debugger for a tensorflow script (`tfevents.py` can be replaced with the name of your training script).
+1. During job submission (either through the UI, the CLI or the SDK) use the debugpy command to run your python script. For example, the following screenshot shows a sample command that uses debugpy to attach the debugger for a tensorflow script (`tfevents.py` can be replaced with the name of your training script).
 
 :::image type="content" source="./media/interactive-jobs/use-debugpy.png" alt-text="Screenshot of interactive jobs configuration of debugpy":::