One of the biggest challenges in real-world machine learning is that supervised models require labeled data—yet in many practical scenarios, the data you start with is almost always unlabeled. Manually annotating thousands of samples isn’t just slow; it’s expensive, tedious, and often impractical. This is where active learning becomes a game-changer. Active learning is a
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