How simple (but clever) algorithms can find label issues in datasets

Show HN: How simple (but clever) algorithms can find label issues in datasets

Operating in show hn launch, How simple (but clever) algorithms can find label issues in datasets operates.

Profile

I built Vizzy as a hackathon project, with the goal of explaining how relatively simple (but clever) algorithms can be a powerful tool to automatically find issues in datasets, including label errors and out-of-distribution data.Vizzy uses a JavaScript port of (a part of) https://github.com/cleanlab/cleanlab, which implements the algorithms described in https://arxiv.org/abs/1911.00068.There are other neat technical nuggets in the implementation of Vizzy as well, including ML model training in the browser (using features from a pretrained ResNet-18, performing truncated SVD, and using an SVM model for speed). If you’re interested in the details of how Vizzy works, check out this blog post: h

As a business in show hn launch, How simple (but clever) algorithms can find label issues in datasets is listed here with the public details available about it.

Directory data places it at the Show HN launch stage.

Website: playground.cleanlab.ai