A common definition of transfer learning is:
"Transfer learning is the improvement of learning in a new task through the transfer of knowledge from a related task that has already been learned."
— Chapter 11: Transfer Learning, Handbook of Research on Machine Learning Applications, 2009.
This raises the question, when a task can be termed "related". Let's assume a neural networks is trained to estimate house prices for american houses. Could it be called transfer learning, if I retrain/finetune the model to estimate european house prices? Is it still the same task or can it be considered a separate task?