One-shot learning is often a machine learning paradigm aiming to recognize objects or styles from a restricted selection of training examples, typically just only one instance.Learners may also disappoint by "learning the wrong lesson". A toy illustration is that a picture classifier trained only on shots of brown horses and black cats may conclude