Bootstrapping Labels via ___ Supervision & Human-In-The-Loop
Read OriginalThis article discusses techniques for bootstrapping training labels in machine learning when labeled datasets are scarce. It covers semi-supervised learning (using pseudo-labels) and active learning (using human-in-the-loop for uncertain samples), citing real-world applications from companies like DoorDash, Facebook, Google, and Apple.
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