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Integrate SageMaker Data Wrangler into your MLOps workflows with Amazon SageMaker Pipelines, AWS Step Functions, and Amazon Managed Workflow for Apache Airflow (MWAA)

Home Page: https://aws.amazon.com/sagemaker/data-wrangler/

License: MIT No Attribution

Python 19.77% Jupyter Notebook 80.23%

sm-data-wrangler-mlops-workflows's Introduction

Integrate SageMaker Data Wrangler into your MLOps workflows

Latest Version License: MIT

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Get Started

  1. Setup an Amazon SageMaker Studio domain.

  2. Log-on to Amazon SageMaker Studio. Open a terminal from File menu > New > Terminal

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  3. Clone this repository

git clone https://github.com/aws-samples/sm-data-wrangler-mlops-workflows.git data-wrangler-pipelines
  1. Open the 00_setup_data_wrangler.ipynb file and follow instructions in the notebook

Setup end-to-end MLOps Pipelines

Security

See CONTRIBUTING for more information.

License

This library is licensed under the MIT-0 License. See the LICENSE file.

sm-data-wrangler-mlops-workflows's People

Contributors

amazon-auto avatar anjanvb avatar awsganpath avatar rodalarcon avatar

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