Chapter 10. Multilayer Perceptron
The concept of artificial neural networks is rooted in biology with the idea of mimicking some of the brain's functions. Computer scientists thought that such a concept could be applied to the broader problem of parallel processing [10:1]. The key question in the 1970s was: how can we distribute the computation of tasks across a network or cluster of machines without having to program each machine? One simple solution consists of training each machine to execute the given tasks. The popularity of neural networks surged in the 1990s.
At its core, a neural network is a nonlinear statistical model that leverages the logistic regression to create a nonlinear distributed model.
Note
Deep learning:
Deep learning techniques (introduced in the next chapter) extend the concept of artificial neural networks. This chapter should be regarded as the first part of the presentation of an algorithm generally associated with deep learning.
In this chapter, you will move beyond...