Feature suggestion -- add support to sagemaker endpoint for end2end sample purpose

I have tried to workout an end-2-end example with iot events sample,
https://github.com/aws-samples/aws-iot-events-accelerators

What I have found is the existing sample for predictive-maintenance only support batch processing to do prediction, while I was trying to add endpoint to the trained model, it failed.

Tried to dig the root reason, sound like the transform_fn function in this sample hardcoded to decode the payload which causing lambda ->apiGateway json payload fail (as while calling the api endpoint, it's trying to passing through json string and won't support binary python json object which is hardcoded in transform_fn function implemented here.

BTW, I don't know why the sample deployed by cfn do not allow me to modify the script, I tried to modify the transform_fn but failed even I gave enough access to the notebook execution role.

Start with the predictive-maintenance sample's transform_fn and the CloudFormation-deployed script, then reproduce the JSON request path from Lambda through API Gateway to the SageMaker endpoint. Done means the end-to-end IoT Events example can invoke the trained model through an endpoint with the payload format described in the issue, while batch prediction remains supported.

Written by the indexing model from the issue text.