addressing PR comments

Author: MadhuM02

articles/machine-learning/how-to-auto-train-image-models.md

@@ -336,8 +336,8 @@ You can control the resources spent on your AutoML Image training job by specify
 
 Parameter | Detail
 -----|----
-`max_trials` |  Required parameter for maximum number of configurations to sweep. Must be an integer between 1 and 1000. When exploring just the default hyperparameters for a given model algorithm, set this parameter to 1.
-`max_concurrent_trials`| Maximum number of runs that can run concurrently. If not specified, all runs launch in parallel. If specified, must be an integer between 1 and 100.  <br><br> **NOTE:** The number of concurrent runs is gated on the resources available in the specified compute target. Ensure that the compute target has the available resources for the desired concurrency.
+`max_trials` |  Parameter for maximum number of configurations to sweep. Must be an integer between 1 and 1000. When exploring just the default hyperparameters for a given model algorithm, set this parameter to 1. default value is 1.
+`max_concurrent_trials`| Maximum number of runs that can run concurrently. If not specified, all runs launch in parallel. If specified, must be an integer between 1 and 100.  <br><br> **NOTE:** The number of concurrent runs is gated on the resources available in the specified compute target. Ensure that the compute target has the available resources for the desired concurrency. default value is 1.
 `timeout_minutes`| The amount of time in minutes before the experiment terminates. If none specified, default experiment timeout_minutes is seven days (maximum 60 days)
 
 # [Azure CLI](#tab/cli)

articles/machine-learning/tutorial-auto-train-image-models.md

@@ -324,7 +324,7 @@ In this example, we will train an object detection model with `yolov5` and `fast
 
 ### Job Limits
 
-You can control the resources spent on your AutoML Image training job by specifying the `timeout_minutes`, `max_trials` and the `max_concurrent_trials` for the job in limit settings.[detailed description on Job Limits parameters](./how-to-auto-train-image-models.md#job-limits).
+You can control the resources spent on your AutoML Image training job by specifying the `timeout_minutes`, `max_trials` and the `max_concurrent_trials` for the job in limit settings. PLease refer to [detailed description on Job Limits parameters](./how-to-auto-train-image-models.md#job-limits).
 # [Azure CLI](#tab/cli)
 
 [!INCLUDE [cli v2](../../includes/machine-learning-cli-v2.md)]