Transfer learning

Transfer learning is the practice of reusing a model trained on one task or dataset as the starting point for a different but related task, reducing the data and computation needed.

Transfer learning sits in the Foundations part of the Agentik {OS} glossary, which defines the words used to build and run AI agent systems.