Build a Serverless News Data Pipeline using ML on AWS Cloud
KDnuggets
NOVEMBER 18, 2021
This is the guide on how to build a serverless data pipeline on AWS with a Machine Learning model deployed as a Sagemaker endpoint.
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KDnuggets
NOVEMBER 18, 2021
This is the guide on how to build a serverless data pipeline on AWS with a Machine Learning model deployed as a Sagemaker endpoint.
KDnuggets
NOVEMBER 18, 2021
This is the guide on how to build a serverless data pipeline on AWS with a Machine Learning model deployed as a Sagemaker endpoint.
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
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The path in the processing container must begin with /opt/ml/processing/. Note: /opt/ml and all its subdirectories are reserved by SageMaker. When building your Processing Docker image, don't place any data required by your container in these directories. More on this is discussed later. Get the input and output filepath.
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