Why Squeaky-Clean Datasets Break Production Vision Models
Over-cleaning training data strips structured real-world noise, leaving vision models brittle. Build a data preservation list before running cleaning sprints.
Written by
Hacker-in-Residence at The Employable Data Scientist
I'm Harpreet Sahota, Hacker-in-Residence at The Employable Data Scientist, a technical consultancy for AI and developer-tool teams, and host of the Artists of Intelligence podcast. I write about AI engineering, computer vision, agent evaluation, and physical AI, with working code and real numbers. Before that, I led developer relations at Voxel51 and Deci AI.
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