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Semi-supervised learning, which mixes supervised and unsupervised learning by making use of each labeled and unlabeled data to train AI versions for classification and regression tasks.Danger actors can target AI designs for theft, reverse engineering or unauthorized manipulation. Attackers could possibly compromise a design’s integrity by tamper