def get_pipeline()

in ML Pipelines scripts/pipeline.py [0:0]


def get_pipeline(
    region,
    sagemaker_project_arn=None,
    role=None,
    default_bucket=None,
    model_package_group_name="CustomerChurnPackageGroup",  # Choose any name
    pipeline_name="CustomerChurnDemo-p-ewf8t7lvhivm",  # You can find your pipeline name in the Studio UI (project -> Pipelines -> name)
    base_job_prefix="CustomerChurn",  # Choose any name