Transfer learning for Deep Neural Networks using TensorFlow
A practical and hands-on example to know how to use transfer learning using TensorFlow.
In this article, we will learn how to use transfer learning for a classification task.
One of the most powerful ideas in deep learning is that we can take the knowledge that a neural network has learned from one task and apply that knowledge to another task. This is called transfer learning.
Transfer learning makes sense when we have a lot of data for the problem we are transferring from and usually relatively less data for the problem we are transferring the knowledge to.
As the first step lets import required modules and load the cats_vs_dogs dataset which is a TensorFlow Dataset. We will consider only 20% of the dataset, as we want to experiment with the usage of transfer learning when the training data is less.
Note: I prefer explaining the code using comments in the code snippets.