Migration is learning on a large database of pre-training model, then this model pre-trained for other tasks, somewhat similar to Word Embedding NLP in.
For example, suppose you have a trained ML A model to identify pictures of animals that you can use to train the model A picture identification dog D. On the data, D training need to add some extra layers to A, but significantly reduces the amount of data required training D.