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The standard data-centric AI package for data quality and ML
cleanlab helps you clean data and labels by automatically detecting issues in a ML dataset. To facilitate machine learning with messy, real-world data, this data-centric AI package uses your existing models to estimate dataset problems that can be fixed to train even better models. cleanlab cleans your data's labels via state-of-the-art confident learning algorithms, published in this paper and blog. See some of the datasets cleaned with cleanlab at labelerrors.com.
Adala is a data-centric AI framework focused on dataset curation, annotation, and validation. It helps AI teams manage high-quality training datasets by providing tools for data auditing, error detection, and quality assessment.