### Description

Today, Amazon provider package supports SageMaker operators for a few operations, like training, tuning, pipelines, but it lacks the support for SageMaker Notebook instances. Boto3 provides necessary APIs to [create notebook instance](https://boto3.amazonaws.com/v1/documentation/api/latest/reference/services/sagemaker/client/create_notebook_instance.html), [start notebook instance](https://boto3.amazonaws.com/v1/documentation/api/latest/reference/services/sagemaker/client/start_notebook_instance.html), [stop network instance](https://boto3.amazonaws.com/v1/documentation/api/latest/reference/services/sagemaker/client/stop_notebook_instance.html) and [delete notebook instance](https://boto3.amazonaws.com/v1/documentation/api/latest/reference/services/sagemaker/client/delete_notebook_instance.html). Leveraging these APIs, we should add new operators to SageMaker set under Amazon provider. At the same time, having a sensor (synchronous as well as deferrable) for notebook instance execution that utilizes [describe notebook instance](https://boto3.amazonaws.com/v1/documentation/api/latest/reference/services/sagemaker/client/describe_notebook_instance.html) and waits for Stopped/Failed status would help with observability of the execution.

### Use case/motivation

Data Scientists are orchestrating ML use cases via Apache Airflow. A key component of ML use cases is running Jupyter Notebook on SageMaker. Having built-in operators and sensors would make it easy for Airflow users to run Notebook instances on SageMaker.

### Related issues

_No response_

### Are you willing to submit a PR?

- [ ] Yes I am willing to submit a PR!

### Code of Conduct

- [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

"""Parse the integer fields to ints in case the config is rendered by Jinja and all fields are str."""
        for field in self.integer_fields:
            self.parse_integer(self.config, field)
    def expand_role(self) -> None:
        """Call boto3's `expand_role`, which expands an IAM role name into an ARN."""
    def preprocess_config(self) -> None:
        """Process the config into a usable form."""
        self._create_integer_fields()
        self.log.info("Preprocessing the config and doing required s3_operations")
        self.hook.configure_s3_resources(self.config)
        self.parse_config_integers()
        self.expand_role()
        self.log.info(
            "After preprocessing the config is:\n %s",
            json.dumps(self.config, sort_keys=True, indent=4, separators=(",", ": ")),
        )
    def _create_integer_fields(self) -> None: