Introduction
Having explored the depths of the Multi-Layer Perceptron (MLP) in our previous chapter with the Fashion-MNIST dataset, we now pivot to a more intricate and visually complex challenge. This chapter marks our transition from the primarily tabular, grayscale world of Fashion-MNIST to the colorful and diverse realm of the CIFAR-10 dataset. Here, we elevate our focus to Convolutional Neural Networks (CNNs), a class of deep neural networks that are revolutionizing the way we approach image classification tasks.
Our journey through the MLP chapter provided a strong foundation for understanding the basics of neural networks and their application in classifying simpler, grayscale images. Now, we step into a more advanced territory where CNNs reign supreme. The CIFAR-10 dataset, with its array of 32x32 color images across 10 different classes, presents a unique set of challenges that MLPs are not best suited to address. This is where CNNs, with their ability to capture spatial...
