fix comments

Author: iamrk04

articles/machine-learning/how-to-automl-forecasting-faq.md

@@ -143,11 +143,11 @@ If your AutoML forecasting job fails, you'll see an error message in the studio
 Model from forecasting training jobs can be deployed in either of the two ways:
 
 1. Online Endpoint
-    - Please refer [this link](./how-to-deploy-automl-endpoint.md) to do online deployment.
-    - Please check the scoring file used in the deployment or click on the "Test" tab on the endpoint page in the studio to understand the structure of input that is expected by the deployment.
+    - Please refer [this link](./how-to-deploy-automl-endpoint.md) for online deployment.
+    - You can check the scoring file used in the deployment or click on the "Test" tab on the endpoint page in the studio to understand the structure of input that is expected by the deployment.
     - You can refer [this notebook](https://github.com/Azure/azureml-examples/blob/main/sdk/python/jobs/automl-standalone-jobs/automl-forecasting-task-energy-demand/automl-forecasting-task-energy-demand-advanced-mlflow.ipynb) to see an example.
 2. Batch Endpoint
-    - Please refer [this link](./how-to-use-batch-endpoint.md) to do batch deployment.
+    - Please refer [this link](./how-to-use-batch-endpoint.md) for batch deployment.
     - It requires you to develop a custom scoring script.
     - You can refer [this notebook](https://github.com/Azure/azureml-examples/blob/main/sdk/python/jobs/automl-standalone-jobs/automl-forecasting-orange-juice-sales/automl-forecasting-orange-juice-sales-mlflow.ipynb) to see an example.
 
@@ -160,7 +160,7 @@ For UI deployments, we encourage to use either of the two options:
 **Please don't use the 1st option i.e. "Real-time-endpoint (quick)"**.
 
 > [!NOTE]
-> As of now, we don't support deploying MLflow model from forecasting training jobs, neither through SDK, nor through CLI, nor through UI. You will run into errors if you try this. This feature will be available very soon.
+> As of now, we don't support deploying MLflow model from forecasting training jobs through SDK, CLI, or UI. You will run into errors if you try this. This feature will be available very soon.
 
 ## What is a workspace / environment / experiment/ compute instance / compute target?