New SageMaker Notebook for Building machine learning workflows with Amazon SageMaker Processing and AWS Step Functions Data Science SDK

Hi,
I'd like to add the following example notebook to support an upcoming blog post featuring the use of Step Functions Data Science SDK's new ProcessingStep to launch SageMaker Processing Jobs. It has gone through a code review [see here](https://issues.amazon.com/AML-79067) and open source review [see here](https://t.corp.amazon.com/P38150419).
The notebook has been tested manually (not with the MEAD CLI tool) in the following regions:
us-east-1
us-east-2
us-west-1
us-west-2
ca-central-1
eu-central-1
sa-east-1

Description of changes:
I added an example notebook that uses the Step Functions Data Science SDK’s ProcessingStep and TrainingStep to build a machine learning workflow that does pre-processing of the data set using new ProcessingStep , trains the model using this dataset and then evaluates the quality of the Model using again the ProcessingStep.
By submitting this pull request, I confirm that you can use, modify, copy, and redistribute this contribution, under the terms of your choice.

The issue proposes a new SageMaker example notebook using ProcessingStep and TrainingStep; no file path or test is named. Start by locating the relevant notebook examples and reviewing the Step Functions Data Science SDK workflow, then verify the preprocessing, training, and evaluation flow in the listed AWS regions. Done means the notebook supports the described workflow and has been manually tested.

Written by the indexing model from the issue text.