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Semi-supervised learning is the type of machine learning that is not commonly talked about by data science and machine learning practitioners but still has a very important role to play. In this type of learning, you will have a small amount of labeled data and a large amount of unlabeled data when training a model that makes a prediction. The latest version of scikit-learn (0.24) has introduced a new self-training implementation for Semi-Supervised learning called SelfTrainingclassifier. SelfTrainingClassifier can be used with any supervised classifier that can return probability estimates.