For example, an algorithm could possibly be fed a scaled-down amount of labeled speech data after which experienced on the much bigger list of unlabeled speech data in order to produce a machine learning model able to speech recognition.Learners could also disappoint by "learning the incorrect lesson". A toy case in point is the fact that an image