The article describes an approach to computer modeling of a neural network. To simulate a neural network, it is necessary to collect a large amount of data about the simulated object, identify its features, create an algorithm that is a set of operations performed on a computer. The function of neural networks is based on classification (sorting), prediction and recognition of objects or events. Modeling neural networks can be carried out by collecting data about an object, highlighting its distinctive features and creating an algorithm using the example of Iris-Fisher flowers. The article also includes a description of the execution of a neural network design task and the use of machine learning algorithms for data mining in an MS Excel spreadsheet processor for teaching lessons.