High expenditures on pre-school education in GDP and average annual expenditures per child in different countries depend not only on public investment. Productive public-private partnerships are also of great importance in the pre-school education and education of children. The successful implementation of social programmes and targeted assistance to families, and the creation of working conditions for women with young children, demonstrate the important role of the State in increasing their pre-school education.
The paper considers the problem of forecastingthe company's share price in the conditions of playing on the stock exchange using artificial neural networks. An artificial neural network of direct propagation is used. The method of reverse error propagation is selected for the training method. A wide range of experiments was conducted on a set of data that covers the summer period of stock market trading. This makes it possible to analyze and compare the effectiveness of various artificial neural network designs using various activation functions.Artificial neural networkshave been used in the last decade to solve problems of image classification, clustering/classification, function approximation function, prediction /forecasting / forecasting, optimization, contentaddressable memory and control.