In Self-Supervised Learning - AIs can do traditionally supervised learning tasks (like classification or regression) using a mix of labeled and unlabeled data.

To a large extent, supervised ML is for domains where automated machine learning does not perform well enough. Scientists add supervision to bring the performance up to an acceptable level.

In supervised learning, a set of input variables, such as blood metabolite or gene expression levels, are used to predict a quantitative response variable like hormone level or a qualitative one ...