Transfer Learning Tutorial. In deep learning transfer learning is a technique whereby a neural network model is first trained on a problem similar to the problem that is being solved. Leverage insights from big data in this tutorial youll see what transfer learning is what some of its applications are and why it is critical skill as a data scientist.
Plot graphs like training accuracy and validation accuracy etc. One way around this is to find a related task b with an abundance of data. Transfer learning in 6 steps obtain the pre trained model.
In deep learning transfer learning is a technique whereby a neural network model is first trained on a problem similar to the problem that is being solved.
You can read more about the transfer learning at cs231n notes. Create a base model. Train the deep neural network on task b and use the model as a starting point for solving task a. Usually the first step is to instantiate the base mode l using one of the architectures such as.