Zero-Shot Learning is an AI approach that enables models to learn to recognise new classes or concepts without explicit training examples. This is achieved by leveraging existing knowledge and transferring it to unseen classes. Zero-Shot Learning is useful when acquiring labelled data for all possible classes is challenging or unfeasible.
Ensemble Learning involves combining multiple Machine Learning models to achieve superior performance and accuracy. By leveraging the “wisdom of the crowd,” Ensemble Learning mitigates…