Meta-Learning

Meta-learning focuses on developing algorithms that can adapt and improve their learning processes based on previous experiences. The goal is to enhance the efficiency of learning by enabling models to generalize across various tasks and datasets. This approach is particularly beneficial in situations with limited data, as it allows models to leverage prior knowledge to accelerate training and improve performance.