One of the biggest goals of deep learning is to train models that have gained generalized knowledge. Generalization is essential because it ensures the model has learned meaningful patterns and can make accurate predictions or decisions when faced with new or unseen data. Training such models often requires a considerable amount of labeled data. However, such data can be costly, labor-intensive, and sometimes impossible.