Hands-On Transfer Learning with Python

Transferring knowledge

Since this chapter and book is focused upon transfer learning, let's quickly get on with the actual task of leveraging and transferring learned information. We have discussed different state-of-the-art CNN architectures in the previous section. Let's now leverage the VGG-16 model, trained on ImageNet, to classify images from the CIFAR-10 dataset. The code for this section is available in the IPython Notebook CIFAR10_VGG16_Transfer_Learning_Classifier.ipynb.

ImageNet is a huge visual dataset with over 20,000 different categories. CIFAR-10, on the other hand, is restricted to only 10 non-overlapping categories. A powerful network like VGG-16 requires immense computational power and time to train to perform better than ...