Introduction to Deep Neural Networks
摘要
In this chapter, we introduce the simplest deep learning architecture used in practice, which is known as the multilayer perceptron (MLP). We will discuss its various components, its ability to approximate functions with different regularity (universal approximation results), and the various training paradigms to learn the various parameters (and hyperparameters) without overfitting the training dataset.