The purpose of the study is to confirm the feasibility of using machine learning methods to predict the behavior of the foreign exchange market. The article examines the theoretical and practical aspects of the implementation of artificial neural networks in the process of Internet trading. We studied the features of constructing automated trading advisors that perform trading operations based on the forecast of neural networks in combination with indicator signals. As a result, a hybrid system has been built that has a high-precision forecast and allows you to make a profit with the correct selection of parameters.

One of the strategic objectives of education is the development of emotional intelligence. The paper examines the relationship between readiness to forgive and emotional intelligence with the level of subjective control. The study of emotional intelligence was carried out according to the method “Emotional intelligence” (N. Hall), the study of the level of subjective control was carried out according to the method of J. Rotter. To determine the level of readiness for forgiveness, the author's questionnaire "Readiness for forgiveness" was compiled. Readiness for forgiveness creates conditions for the development of a personality as a forgiver as well as the personality of the forgiven person. It appears as a result of deeper understanding of the traumatic situation and the reasons for its occurrence. Readiness to forgive, to our opinion, is a base tool for the transformation of emotional manifestation. We found a significant correlation between the integrative index of emotional intelligence and a level of a readiness for forgiveness. Subjects with a high readiness for forgiveness are capable of efficient regulation of their emotional sphere. Various forms of organization of group work help students to adjust their ideas about readiness for forgiveness, which contributes to the development of emotional intelligence, harmonization of both intrapersonal and interpersonal space. Formation of a deeper and adequate understanding of readiness for forgiveness is an important task of the education.

The article deals with the problem of determining the rheological parameters of polymers from stress relaxation curves using the CatBoost machine learning algorithm. The model is trained on theoretical curves constructed using the non-linear Maxwell-Gurevich equation. A comparison is made with other methods, including the classical algorithm, non-linear optimization methods and artificial neural networks.