Transfer learning aims to test how well a deep learning system can solve problems similar to the ones it's already studied. For example, researchers might take a program that was trained to ...

Summary of Transfer Learning: Transfer learning is a powerful technique in machine learning, allowing models to adapt to new tasks efficiently by leveraging pre-trained knowledge.

Deep learning algorithms are modeled after the structure and function of the human brain, making use of multiple layers of artificial neurons (hence "deep" learning).

What is transfer learning in deep learning? Transfer learning aims to test how well a deep learning system can solve problems similar to the ones it's already studied.