Technique
Transfer Learning
Reusing pre-trained models for new but related tasks
What is Transfer Learning?
Transfer Learning is a machine learning technique where a model trained on one task is repurposed or fine-tuned for a second related task. This approach leverages knowledge gained from one problem to solve different but related problems, often requiring less data and training time.
Key Points
1
Leverages pre-trained models
2
Requires less training data
3
Faster training time
4
Improves performance on small datasets
Practical Examples
Fine-tuning GPT models
Using ImageNet pre-trained CNNs
BERT for specific NLP tasks
Domain adaptation