In this tutorial, we will reuse the feature extraction capabilities from powerful image classifiers trained on ImageNet and simply train a new classification layer on top. Transfer learning is a technique that shortcuts much of this by taking a piece of a model that has already been trained on a related task and reusing it in a new model.