Differences Between Semi Supervised Learning and Self Supervised Learning !
Semi Supervised Learning Definition Semi-supervised learning (SSL) is a machine learning technique that combines supervised and unsupervised learning. Use of Data It uses both labeled and unlabeled data to train artificial intelligence (AI) models for a variety of tasks, including classification, regression, clustering, and association. Useful SSL is useful in situations where it's difficult or expensive to get enough labeled data, but there's a lot of unlabeled data that's easy to get. Some examples of SSL: Identifying fraud: SSL can be used to train systems to identify fraud or extortion in finance. Classifying web content: SSL can be used to classify large amounts of web content. SSL is effective because it: Reduces the need for manual annotation, Cuts down on data preparation time, and Shows promising results for classification tasks. In SSL, you train an initial model on a small number of labeled samples, and then use it on a larger number of unl