updating readme formatting

README.md

@@ -24,57 +24,63 @@ It provides:
 - [Customer Churn Pipeline on AWS](#customer-churn-pipeline-on-aws)
   - [Table of contents](#table-of-contents)
   - [Getting Started](#getting-started)
+  - [Clean up](#clean-up)
   - [Read The Docs](#read-the-docs)
   - [Solution Architecture](#solution-architecture)
   - [Contributing](#contributing)
 
 ## Getting Started
 
-    # Step 1 - Modify default Parameters
+1. **Step 1** - Modify default Parameters
 
-Update the `.env` file in the main directory. 
-To run with Cox proportional hazard modeling instead of binary logloss set `COXPH` to '"positive"`.
+Update the `.env` file in the main directory.
+To run with Cox proportional hazard modeling instead of binary logloss set `COXPH` to `"positive"`.
 
-`S3_BUCKET_NAME="{YOU_BUCKET_NAME}"`\
-`REGION="{YOUR_REGION}"`\
-`STACK_NAME="{YOUR_STACK_NAME}"`\
-`COXPH="{negative|positive}"`
+```shell
+S3_BUCKET_NAME="{YOU_BUCKET_NAME}"
+REGION="{YOUR_REGION}"
+STACK_NAME="{YOUR_STACK_NAME}"
+COXPH="{negative|positive}"
+```
 
-    # Step 2 - Deploy the infrastructure
+2. **Step 2** - Deploy the infrastructure
 
 `./standup.sh`
 
-    # Step 3 - Update the pending GitHub Connections
+3. **Step 3** - Update the pending GitHub Connections
 
 To configure the [Github connection](https://docs.aws.amazon.com/codedeploy/latest/userguide/integrations-partners-github.html) manually in the CodeDeploy console, go to Developer Tools -> settings -> connections. This is a one time approval. Install as App or choose existing.
 
   <p align="center">
   <img src="images/UpdateConn.png" width="899" class="centerImage">
   </p>
 
-    # Step 4 - Release change in churn pipeline for the first time
+4. **Step 4** - Release change in churn pipeline for the first time
 
   <p align="center">
   <img src="images/ReleaseChange.png" width="899" class="centerImage">
   </p>
 
-    # Step 4 - Once the build succeeds, navigate to Step Functions to verify completion
+5. **Step 5** - Once the build succeeds, navigate to Step Functions to verify completion
 
-    # Step 5 - Trigger Inference pipeline. Batch Inference can be automated using cron jobs or S3 triggers as per business needs.
+6. **Step 6**- Trigger Inference pipeline. Batch Inference can be automated using cron jobs or S3 triggers as per business needs.
 
-`AWS_REGION=$(aws configure get region)`
+```shell
+AWS_REGION=$(aws configure get region)
+aws lambda --region ${AWS_REGION} invoke --function-name invokeInferStepFunction --payload '{ "": ""}' out
+```
 
-`aws lambda --region ${AWS_REGION} invoke --function-name invokeInferStepFunction --payload '{ "": ""}' out`
-
-    # Clean up
+## Clean up
 
 `./delete_resources.sh`
 
-    This does not delete the S3 bucket. In order to delete the bucket and the contents in it, run the below -
+This does not delete the S3 bucket. In order to delete the bucket and the contents in it, run the below -
 
-`source .env`\
- `accountnum=$(aws sts get-caller-identity --query Account --output text)`\
- `aws s3 rb s3://${S3_BUCKET_NAME}-${accountnum}-${REGION} --force`
+```shell
+source .env
+ accountnum=$(aws sts get-caller-identity --query Account --output text)
+ aws s3 rb s3://${S3_BUCKET_NAME}-${accountnum}-${REGION} --force
+```
 
 ## [Read The Docs](https://awslabs.github.io/aws-customer-churn-pipeline/)