aws-samples/sm-data-wrangler-mlops-workflows
Integrate SageMaker Data Wrangler into your MLOps workflows with Amazon SageMaker Pipelines, AWS Step Functions, and Amazon Managed Workflow for Apache Airflow (MWAA)
This helps MLOps engineers integrate SageMaker Data Wrangler's data preparation capabilities directly into their automated machine learning workflows. It takes your raw data, processes it using Data Wrangler flows, and then feeds the cleaned, transformed data into your SageMaker Pipelines, AWS Step Functions, or Apache Airflow pipelines. This is for MLOps engineers and machine learning platform developers who manage end-to-end ML operations.
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Use this if you need to operationalize and automate your data preparation steps performed in SageMaker Data Wrangler as part of a larger machine learning pipeline.
Not ideal if you are looking for a standalone data cleaning tool or if your ML pipelines are not built on SageMaker Pipelines, AWS Step Functions, or Apache Airflow.
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MIT-0
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Last pushed
Sep 01, 2022
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