DC-Check: A Data-Centric AI checklist to guide the development of reliable machine learning systems. (arXiv:2211.05764v1 [cs.LG])

While there have been a number of remarkable breakthroughs in machine
learning (ML), much of the focus has been placed on model development. However,
to truly realize the potential of machine learning in real-world settings,
additional aspects must be considered across the ML pipeline. Data-centric AI
is emerging as a unifying paradigm that could enable such reliable end-to-end
pipelines. However, this remains a nascent area with no standardized framework
to guide practitioners to the necessary data-centric considerations or to
communicate …

arxiv checklist data data-centric development guide machine machine learning systems