Few-Shot Learning

What is Few-Shot Learning?

A learning paradigm where a model learns to recognize a new class from only a handful of examples (the 'support set').

Where did the term "Few-Shot Learning" come from?

Meta-learning / learning to learn.

How is "Few-Shot Learning" used today?

Essential when data is scarce.

Related Terms

• Machine Learning
• Zero-Shot Learning (ZSL)