Introduction to transfer learning
As humans, it is easy for us to transfer knowledge gained from one task or activity to another. For instance, if you have a good grasp of Python (the programming language, not the snake) and you decide to learn Rust, because of your background knowledge in Python, you will find it easier to learn Rust compared to someone who has never written a basic program in any programming language. This is because certain concepts, such as object-oriented programming, have similarities across different programming languages. Transfer learning follows the same principle.
Transfer learning is a technique in which we leverage a model pre-trained on task A to solve a different but related task B. For example, we use a neural network trained on one task and transfer the knowledge gained to multiple related tasks. In image classification, we often use deep learning models that have been trained on very large datasets, such as ImageNet, which is made up of more than...