We’re excited to share with the HN community our open-source Python package for addressing data-quality issues in machine learning, automating tasks like finding label errors in datasets. cleanlab started out as a grad student research project, and it was eventually open-sourced. As we saw data scientists finding the tool useful for real-world applications, and as we did more research that applied the tool to find issues in academic datasets at scale (https://labelerrors.com/), we realized that this was an important real-world problem and decided to spend more time and energy building a useful and usable framework for solving data-quality challenges.
We’d love to hear any ideas or feedback from the HN community, especially from those who face data-quality challenges in their work. We (me, @cgn, and @_jonas), who all have a background in ML research, would also be happy to answer any questions you have related to cleanlab or data-centric AI.
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[ 3.4 ms ] story [ 17.2 ms ] threadWe’d love to hear any ideas or feedback from the HN community, especially from those who face data-quality challenges in their work. We (me, @cgn, and @_jonas), who all have a background in ML research, would also be happy to answer any questions you have related to cleanlab or data-centric AI.