Hosted by Scale

The Learning Curve: Model-in-the-Loop Data Curation

Recorded Jun 16th @ 7PM Coordinated Universal Time

About this event

The Learning Curve: Model-in-the-Loop Data Curation

Scale Nucleus was developed to help ML teams debug their models by debugging their datasets. In this talk, we walk through some of the latest updates and discuss how Nucleus enables you to diagnose model failure cases, to then prioritize what data should be labeled next to improve model performance. We will then walk through a demo of how you can use models to debug data, and data to debug models for model-in-the-loop data curation.

Presented by

Sasha Harrison

Sasha Harrison is a software engineer on the Nucleus team, where she works on building a comprehensive dataset management platform to automate the data work. Previously, she was a Master’s student in Computer Science at Stanford University with a specialization in AI and research interests in algorithmic fairness


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