Multi-Task Learning - What is the difference between multi-task learning and transfer learning?

To put it succinctly, multi-task learning is designed to learn multiple tasks at the same time, whereas transfer learning is about transferring knowledge from one task to another to enhance performance. Both methods hold their own value in machine learning applications, based on the specific context and objectives.