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cleanlab
The standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.
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WorkOS
The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.
For example, [Confident Learning: Estimating Uncertainty in Dataset Labels](https://jair.org/index.php/jair/article/view/12125) was one that didn't need high compute, but significant, able to find large number of mislabelled data in commonly used datasets like CIFAR and ImageNet. It later became [cleanlab](https://github.com/cleanlab/cleanlab).
NOTE:
The number of mentions on this list indicates mentions on common posts plus user suggested alternatives.
Hence, a higher number means a more popular project.
Related posts
- Show HN: Simple (but clever) algorithms can find label issues in datasets
- [D] A simple trick to quickly verify data
- [P] Cleanlab Vizzy — learn how to automatically find label errors and out-of-distribution data
- Show HN: Cleanlab Vizzy – automatically find label errors and bad data
- [D] How to deal with badly labelled data?