In any data analysis task, it is important to understand how the data was collected. With the model that we developed in the previous section, the accuracy dropped from over 90% for the test data to 50% for the 20 fashion item images that were downloaded from the internet. If this difference is not addressed, it will be difficult for this model to generalize well with any fashion items that are not part of the training or test data, and therefore will not be of much practical use. In this section, we will explore improvements to the classification performance of the model.
Performance optimization tips and best practices
Image modification
Looking at the 64 images at the beginning of this chapter reveals some clues as to what...
