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Modyn: DataCentric Machine Learning Pipeline Orchestration MAXIMILIAN BTHER, ETH Zurich, Switzerland TIES ROBROEK, IT University of Copenhagen, Denmark VIKTOR GSTEIGER, ETH Zurich, Switzerland ROBIN

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What is modyn data-centric machine learning?

Modyn data-centric machine learning refers to a methodology that focuses on the importance of data quality and data management in the development of machine learning models, emphasizing the need to optimize and refine datasets for improved model performance.

Who is required to file modyn data-centric machine learning?

Individuals or organizations that develop machine learning models using modyn compliant datasets, or those involved in regulated industries requiring adherence to modyn standards, are typically required to file.

How to fill out modyn data-centric machine learning?

Filling out modyn data-centric machine learning typically involves providing detailed information about the dataset, including its source, structure, any preprocessing applied, as well as validation methods to ensure data integrity.

What is the purpose of modyn data-centric machine learning?

The purpose of modyn data-centric machine learning is to enhance the reliability and effectiveness of machine learning models by promoting best practices in data handling and ensuring that datasets are fit for purpose.

What information must be reported on modyn data-centric machine learning?

Information that must be reported includes dataset provenance, characteristics, data processing methods, data quality assessments, model validation metrics, and any ethical considerations related to data usage.

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