what about differences between the meta and semi-supervised and self-supervised and active and federated and few-shot learning?

what about difference between the meta learning and semi-supervised learning and self-supervised learning and active learning and federated learning and few-shot learning? in application and in definition? Pros and cons?

Topic few-shot-learning federated-learning meta-learning active-learning semi-supervised-learning

Category Data Science

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