Supervised learning starts with training data that are tagged with the correct answers (target values). After the learning process, you wind up with a model with a tuned set of weights, which can ...

Similar semi-supervised learning schemes can be used for other kinds of semi-supervised learning, including natural language processing, classification, and regression on several services.