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AI & Machine Learning · Intermediate

Transfer Learning

Reusing a model trained on one task as the starting point for a related task.

Definition

Transfer learning leverages representations learned from large datasets so that a new task needs far less data and compute. Typical approaches freeze early layers and retrain later ones, or fine-tune the whole network. Fine-tuning foundation models is a form of transfer learning.

Example

Starting from an ImageNet-pretrained ResNet to classify 500 images of manufacturing defects.

Exam tip

When labeled data is scarce, transfer learning from a pretrained model is usually the best answer.

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