Search Results
2 results for “meta-learning”
Foundations
Few-Shot Learning
Few-shot learning is a machine learning paradigm in which a model learns to perform new tasks or recognise new classes from only a small number of labelled training examples, often just one to five samples per class.
6 min readUpdated May 2026
Foundations
Meta-Learning
A machine learning paradigm in which models learn how to learn, acquiring inductive biases across a distribution of tasks so they can adapt rapidly to new tasks with minimal data.
5 min readUpdated May 2026