Semi-supervised learning is a machine learning paradigm that utilizes both labeled and unlabeled data for model training. It bridges the gap between supervised learning, which uses solely labeled data, and unsupervised learning, which relies entirely on unlabeled data. This approach combines the best of both worlds to create more efficient models. In semi-supervised learning, a […]
