Automatically Fix Data Issues and Label Errors in Most ML Datasets - Cleanlab

Explore a 15-minute conference talk on automatically fixing data issues and label errors in machine learning datasets using Cleanlab. Dive into the open-source Cleanlab framework and Cleanlab Studio, a no-code web interface used by universities and Fortune 500 companies for dataset issue detection and fixing. Learn about the theoretical support behind Cleanlab algorithms for improved accuracy on real-world, messy data. Gain insights from Curtis Northcutt, CEO and co-founder of Cleanlab, as he shares his expertise in machine learning and AI. Discover how these tools can empower data professionals to enhance model performance by addressing data quality challenges in their datasets.

Automatically Fix Data Issues & Label Errors in Most ML Datasets | Cleanlab