When can it be called transfer learning? A common definition of transfer learning is:

&quot;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.&quot;

— Chapter 11: Transfer Learning, Handbook of Research on Machine Learning Applications, 2009.
This raises the question, when a task can be termed &quot;related&quot;.
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?
Good question but rather besides the point.
What I mean is that even though estimating european house prices can be considered the same task (as estimating american house prices), nevertheless in this example the NN was re-purposed using transfer learning methods from another task.
Whether one would like to call the european house prices as same or related task, is not so much the point here (which can become pedantic), but rather if transfer learning methods were used and how succesfull they were.
IMHO