GLOSSARY TERM
What is Transfer Learning?
Reusing a pre-trained model on a new, structurally related problem.
Transfer learning bypasses the massive computational cost of training from scratch. By starting with weights already optimized for general feature extraction, models converge significantly faster on domain-specific datasets.
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