What is fine-tuning?
Fine-tuning is a technique of transfer learning in which the weights of a pretrained neural network are used as the initial values for training a new neural network on a different task. This can improve the performance of the new network by leveraging the knowledge learned from the previous task, especially when the new task has limited data.
Definition
Transfer learning is a technique in machine learning that involves using the knowledge learned from one task to improve the performance on a related but different task. For example, if you have a model that can recognize cars, you can use some of its features to help you recognize trucks. Transfer learning can save you time and resources by reusing existing models instead of training new ones from scratch.
To better understand the concepts of transfer learning and fine-tuning, let’s consider the following example.
Imagine you want to train a computer vision neural network to...
