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Semi-supervised learning, which mixes supervised and unsupervised learning by using both labeled and unlabeled data to practice AI products for classification and regression duties.Like all technologies, types are liable to operational risks like design drift, bias and breakdowns in the governance framework. Still left unaddressed, these risks may