Transfer Learning Explained for Beginners

Transfer learning means that a computer reuses something it has learned from one task for another task.

Imagine you are learning to ride a bicycle. When you then learn to ride a scooter, you can use many skills from riding a bicycle.

It works similarly with computers: they use knowledge from one task to learn faster or better on a new task.

As a result, they need fewer examples and can achieve good results more quickly.

Transfer learning helps computers share their knowledge and not have to start from scratch.