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The article discusses the use of orchestrators in automating machine learning processes and ensuring the reproducibility of results.
The three main orchestrators discussed are Kubeflow Pipelines, Airflow, and Prefect. The article compares the advantages and disadvantages of each orchestrator and concludes that the choice of orchestrator depends on the specific project requirements.
Kubeflow was the preferred choice for the authors due to its CI/CD configuration and containerization advantages. However, Prefect is recommended for small projects or teams with a limited budget, and Airflow is ideal for running a variety of tasks using a mature and developed tool.
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