Summary

In this chapter, we gained insight into simulating typical human brain activities using ANNs. We grasped the fundamental concepts behind ANNs, delving into the creation of a basic neural network architecture. This exploration encompassed elements such as input, hidden, and output layers, connection weights, and activation functions. Our understanding extended to crucial decisions regarding hidden layer count, node quantity within each layer, and network training algorithms.

Then we focused on data fitting and pattern recognition using neural networks. We engaged in script analysis to master the utilization of neural network functions via the command line. We then ventured into the Neural Network Toolbox, featuring algorithms, pre-trained models, and apps for crafting, training, visualizing, and simulating shallow and deep neural networks. The Neural Network Toolbox offers an accessible interface—the Neural Network getting started GUI—which serves as the launchpad...