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Using ML to Improve Labeling Quality on Scale Rapid
Scale Rapid helps ML teams iterate quickly with an on-demand, end-to-end, labeling solution with rapid turnaround times. In this tech talk, we discuss the challenges to build quality infrastructure for crowd management, then discuss the role machine learning can play in:
- Achieving high quality even with subjective tasks
- Flagging potential problems with evaluation tasks
- Suggesting improvements for project health
We'll discuss where ML can accelerate and scale human insights, the challenges of creating generalizable quality mechanisms, and the trade-offs that must be considered between accuracy and generalizability for such ML solutions.
Speakers
Kiko Ilagan
ML Lead, Rapid @ Scale AI
Bryan Chen
Lead Engineer, Rapid @ Scale AI
Zhichun Li
Head of Rapid @ Scale AI
Agenda
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7:00 PM, GMT
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8:00 PM, GMT
Stage 1
Presentation
Using ML to Improve Labeling Quality on Scale Rapid
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Event has finished
April 06, 7:00 PM, GMT
Online
Event has finished
April 06, 7:00 PM, GMT
Online