Add notes for port

EmployeeAttritionPrediction/Code/EmployeeAttritionPredictionOperationalization.Rmd

@@ -281,7 +281,7 @@ A Docker image can be built by using the Dockerfile with
 ```
 docker build -t <image_name> <path_to_the_dockerfile>
 ```
-and run with
+and run with (NOTE the port number should be the same as that is exposed in the dockerfile. In this case, it is 3838.)
 
 ```
 docker run --rm -p 3838:3838 <image_name>
@@ -490,7 +490,7 @@ Kubernetes cluster. This can be done via copy the `config` file located at
 `~/.kube` on master node of the Kubernetes cluster to `~/.kube/` of the local
 machine.
 
-Each of the two applications can be deployed individually as follows.
+Each of the two applications can be deployed individually as follows (NOTE the port number should be the same as that is exposed in the dockerfile. In this case, it is 3838).
 ```
 kubectl run <name_of_deployment> --image <dockerhub_account_name>/<name_of_repo>
 --port=3838 --replicas=3
@@ -614,4 +614,4 @@ The readers can find Dockerfile as well as Shiny R codes in the directories.
 Images built based on them are pre-published on Dockerhub - `yueguoguo/hrdata`
 and `yueguoguo/hrmodel`, corresponding to the data exploration application and
 model creation application, respectively. These images are ready for testing
-on a deployed Kubernetes typed Azure Container Service cluster.
+on a deployed Kubernetes typed Azure Container Service cluster.