AI engineering glossary · ML fundamentals
What is meta-learning?
Meta-learning (also called Learning to learn): Learning how to learn: training across many tasks so that a model can adapt quickly to a new task from very few examples. It is sometimes described as learning the learning procedure itself.
Meta-learning: an example
A model trained on hundreds of small classification tasks can learn a new task, such as recognising a rare disease, from five examples.
Related terms
More ML fundamentals terms
- Model
- Model capacity
- Model selection
- Model variance
- Nested cross-validation
- No free lunch theorem
- Noise
- Non-parametric model
Where you learn it
Meta-learning is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.