Cleanlab's open-source library is the standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.
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A light-weight, flexible, and expressive statistical data testing library
Deepchecks: Tests for Continuous Validation of ML Models & Data. Deepchecks is a holistic open-source solution for all of your AI & ML validation needs, enabling to thoroughly test your data and models from research to production.
Lightweight, extensible data validation library for Python
Data validation toolkit for assessing and monitoring data quality.
Lightweight DataFrame validation decorators for Pandas, Polars, Modin, and PyArrow. No custom types required.
Declarative data quality engine. Define checks in YAML, run anywhere.
Validates tabular CSV data using predefined validations, inspired from its Python homologue "Great Expectations".