Machine and Deep Learning Using MATLAB

5 Neural Networks

Introduction

The idea of using neural networks is relevant when we do not really know the equation that dictates the relationship between the response variable on one side and the set of predictor variables on the other side. In many case studies, we have so many inputs with interrelations and yet we do not know what the response behavior will be. If we have an idea of the equation, it will be better to use the conventional linear and nonlinear regression methods. Consequently, the neural network regression is a kind of stochastic, as opposed to deterministic, model in the sense that it tries to understand different relationships among the players (variables) via recognizing what is called patterns. To demonstrate the game of neural network, a person is assigned a duty to separate the male baby from female baby chicken. The accuracy in predicting the type of baby chicken class is more than 90%. This assigned person makes use of brain neural networks-based recognition using the God-granted natural intelligence. The neural networks-based artificial intelligence more or less mimics one of the primary brain main duties.

Neural networks have found applications in various fields due to their ability to learn from data and make predictions or decisions. Here are some life examples where neural networks are commonly used:

1. Image Recognition: Neural networks are extensively used in applications like facial recognition, object detection, and image classification. They ...