Shallow and Deep Learning Principles

The book "Shallow and Deep Learning Principles" offers a comprehensive analysis of artificial neural networks (ANN) and their ability to predict outcomes through the application of deep and shallow learning principles. The author, Zekâi Sen, first explains the implementation of ANN, which consists of at least three layers: an input layer, an output layer, and a hidden (intermediate) layer. It emphasizes that a suitable architecture must be developed that not only models mathematical rules but also takes into account the variables for actions and reactions that may occur within an event. The book addresses the necessity and reasons for each ANN model and draws comparisons to earlier methods as well as to philosophical-logical rules.