Data Scarcity - How transfer learning deals with the scarcity of data?

By feeding the model existing information, Transfer Learning is able to alleviate the problem of insufficient data. Because of this, it can learn new tasks with less training data. It is possible, for instance, to train a model to recognize a particular dog breed using a smaller dataset if the model has previously been trained on a big dataset of animals.