readme changes for gating criteria (aws#4656)

Co-authored-by: Zhaoqi <jzhaoqwa@amazon.com>

Author: vikeshpandey

.github/PULL_REQUEST_TEMPLATE.md

@@ -8,6 +8,7 @@
 
 _Put an `x` in the boxes that apply. You can also fill these out after creating the PR. If you're unsure about any of them, don't hesitate to ask. We're here to help! This is simply a reminder of what we are going to look for before merging your pull request._
 
+- [ ] I have verified that my PR does not contain any new notebook/s which demonstrate a SageMaker functionality already showcased by another existing notebook in the repository.
 - [ ] I have read the [CONTRIBUTING](https://github.com/aws/amazon-sagemaker-examples/blob/master/CONTRIBUTING.md) doc and adhered to the example notebook best practices
 - [ ] I have updated any necessary documentation, including [READMEs](https://github.com/aws/amazon-sagemaker-examples/blob/master/README.md)
 - [ ] I have tested my notebook(s) and ensured it runs end-to-end

CONTRIBUTING.md

@@ -26,6 +26,7 @@ Before sending us a pull request, please ensure that:
 * You are working against the latest source on the *main* branch.
 * You check the existing open and recently merged pull requests to make sure someone else hasn't already addressed the problem.
 * You open an issue to discuss any significant work - we would hate for your time to be wasted.
+* **NOTE:: If you are submitting an entirely new notebook, please ensure it demonstrates a functionality of SageMaker not yet showcased by any other existing notebook in this repository. If you don't meet this criteria, your PR will be rejected.**
 
 
 ### Pull Down the Code

README.md

@@ -4,14 +4,18 @@
 
 Example Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using Amazon SageMaker.
 
-## :books: Background
+## :books: Read this before you proceed further
 
-[Amazon SageMaker](https://aws.amazon.com/sagemaker/) is a fully managed service for data science and machine learning (ML) workflows.
-You can use Amazon SageMaker to simplify the process of building, training, and deploying ML models.
+Amazon SageMaker examples are divided in two repositories:
 
-The [SageMaker example notebooks](https://sagemaker-examples.readthedocs.io/en/latest/) are Jupyter notebooks that demonstrate the usage of Amazon SageMaker.
+- [SageMaker example notebooks](https://github.com/aws/amazon-sagemaker-examples) is the official repository, containing examples that demonstrate the usage of Amazon SageMaker. This repository is entirely focussed on covering the breadth of features provided by SageMaker, and is maintained directly by Amazon SageMaker team.
 
-The [Sagemaker Example Community repository](https://github.com/aws/amazon-sagemaker-examples-community) are additional notebooks, beyond those critical for showcasing key SageMaker functionality, can be shared and explored by the commmunity.
+- [Sagemaker Example Community repository](https://github.com/aws/amazon-sagemaker-examples-community) is another SageMaker repository which contains additional examples and reference solutions, beyond the examples showcased in the [official repository](https://github.com/aws/amazon-sagemaker-examples). This repository is maintained by community of engineers and solution architects at AWS.
+
+## Planning to submit a PR to this repository? read this first:
+- This repository will only accept notebooks/examples which demonstrate a feature of SageMaker, not yet covered anywhere in this repository. PR submitters are requested to check this before submitting the PR to avoid getting it rejected.
+
+- If you still would like to contribute your example, please submit a PR to [Sagemaker Example Community repository](https://github.com/aws/amazon-sagemaker-examples-community) instead.
 
 
 ## :hammer_and_wrench: Setup