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It works by using historical info as enter to predict new output values. Equipment Understanding consists of each supervised Studying (in which the predicted output for that enter is thought because of labeled info sets) and unsupervised Mastering (where the envisioned outputs are not known as a consequence of the use of unlabeled information sets)