Self-Supervised Learning Methods: Generating Supervisory Signals from Input Data Structure for Representation Learning
IntroductionModern machine learning systems often rely on large labelled datasets, but labelling is expensive, slow, and sometimes impractical. In many real-world settings, organisations collect abundant raw data-text logs, images, audio, sensor readings, clickstreams-yet only a small portion is labelled. Self-supervised learning addresses this gap by creating supervisory signals directly from...


