Chapter 4: Ready-to-Cook Models from Lightning Flash

Building a Deep Learning (DL) model often involves recreating existing architectures or experiments from top-notch research papers in the field. For example, AlexNet was the winning Convolutional Neural Network (CNN) architecture in 2012 for the ImageNet computer vision challenge. Many data scientists have recreated that architecture for their business applications or built newer and better algorithms based on it. It is a common practice to reuse existing experiments on your data before conducting your own experiments. Doing so typically involves either reading the original research paper to code it or tapping into the author's GitHub page to gain an understanding of what's what, which are both time-consuming options. What if the most popular architectures and experiments in DL were easily available for executing various common DL tasks as part of a framework? Meet PyTorch Lightning Flash!

Flash provides out-of-the-box...