In this tutorial, we will expand “Building a CNN Classifier with PyTorch: Part 1” and introduce more advanced techniques that can be leveraged to optimize the performance of your CNN classifier model. We will again be using data from DesignSafe in this tutorial, specifically a dataset from Hurricane Harvey, a category 4 hurricane that hit Texas in August of 2017 and resulted in catastrophic flooding to the Houston metropolitan area. The data set is specifically focused on image classification of homes according to the amount of damage the home received. All images of homes are labeled as C0, C2, or C4 respectively for low, medium or high damage.