Transfer Learning
Training a complex neural network is hard and time-consuming due to the amount of data required for training. Transfer learning helps data scientists transfer part of the knowledge gained by one network to another. This is similar to how humans transfer knowledge from one person to another so that everyone does not have to start learning every new thing from scratch. Transfer learning helps data scientists train neural networks faster and with fewer data points. There are two ways to perform transfer learning depending on the situation. They are as follows:
- Use a pre-trained model: In this approach, we use a pre-trained neural network model and use it to solve the problem at hand. A pre-trained model is a neural network that has been created for a different purpose to the one at hand, has been trained on some other dataset, and has been saved for future reuse. The pre-trained model must be trained on a similar or same dataset to get reasonable accuracy.
- Create a...
