Ключевое слово: «perceptron»

In this work, a theoretical basis will be given about neural networks, as well as their potential. In its practical part, we will create our own neural network for a brighter idea of this technology. The work will be done using a high-level programming language – Python. Assistive tools in this case will be the activator function – sigmoid, as well as the back propagation method for aligning synaptic weights. As a result, we have successfully created NN, which is able to predict the output data from the input data. The developed NN can be considered as a convenient tool for practical understanding of how neural networks work.