cleanlab
An open-source data-centric AI library for automatically detecting and fixing data quality issues in machine learning datasets.
What is cleanlab?
Cleanlab is an open-source Python library that automates data quality improvement for machine learning. It detects issues like mislabeled data, outliers, and duplicates in datasets, enabling practitioners to train more robust models without changing their modeling code. The library applies data-centric AI principles by using existing model predictions to estimate and fix dataset problems.
Machine learning engineers, data scientists, and researchers working with real-world, messy datasets who want to improve model performance through better data quality. It's particularly valuable for teams dealing with noisy labels, multi-annotator data, or seeking to implement active learning workflows.
Cleanlab provides provable, model-agnostic data cleaning with minimal code changes, backed by peer-reviewed research. Unlike manual inspection or custom scripts, it offers automated, scalable issue detection across diverse data types and ML tasks, often yielding significant performance gains without altering the underlying model architecture.
Overview
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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