Summary

We got a taste of basic MLPs and CNNs in this chapter, which are the building blocks of DL. We learned that by using the PyTorch Lightning framework, we can easily build our models. While MLPs and CNNs may sound like basic models, they are quite advanced in terms of business applications, and many companies are just warming up to their industrial use. Neural Networks are used very widely as classifiers on structured data for predicting users' likes or propensity to respond to an offer or for marketing campaign optimization, among many other things. CNNs are also widely used in many industrial applications, such as counting the number of objects in an image, recognizing car dents for insurance claims, facial recognition to identify criminals, and so on.

In this chapter, we saw how to build the simplest yet most important XOR operator using an MLP model. We further extended the concept of MLPs to build our first CNN DL model to recognize images. Using PyTorch Lightning...