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Machine Learning

Self-Supervised Learning: How Models Learn Without Labeled Data

Self-supervised learning trains models to pull their own supervision from unlabeled text, images, audio, and video, using techniques like contrastive learning, masked modeling, and autoregressive prediction to build the representations behind today's language, vision, and multimodal models.

Dario Radečić