Sensors

Semi-supervised learning is a machine learning approach that leverages a small amount of labeled data along with a large quantity of unlabeled data to train models. This technique enhances learning efficiency, especially when labeling data is costly or time-consuming. It combines the strengths of supervised and unsupervised learning, improving accuracy and generalization in tasks such as image recognition and natural language processing.