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3 results for “transfer 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
Foundations
Transfer Learning
Transfer learning is a machine learning technique in which a model pre-trained on one task or dataset is adapted for a different but related task, enabling high performance with significantly less data and compute than training from scratch.
6 min readUpdated May 2026