Data Labeling: The Authoritative Guide

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Introduces data labeling for ML, its importance, types of data (images, video, 3D, audio, text), ML categories (supervised, unsupervised, reinforcement), and annotation strategies (automated, human-only, human-in-the-loop). Discusses workforce sourcing (in-house, third-party).