Category: Education

Meta-learning for few-shot learning is a paradigm in machine learning that focuses on training models to rapidly adapt to new tasks with limited data. Few-shot learning scenarios involve training models to perform well on tasks with only a small number of examples per class. Meta-learning approaches aim to leverage knowledge gained from learning multiple tasks to improve the efficiency of learning new tasks quickly.