MACHINE LEARNING IN ECONOMIC SECURITY ISSUES
The article is devoted to the review of machine learning methods and analysis of their applicability in the tasks of ensuring economic security at various hierarchical levels of the national economy. The paper shows that in modern economic realities, artificial intelligence and machine learning methods are becoming the most important tool for solving management problems. The operational analysis and forecasting of economic security requires the use of modern methods for predicting threats and selecting effective strategies to prevent their consequences. The article analyzes publications on the use of machine learning methods in economic research, presents the key tasks of machine learning in the context of ensuring the economic security of systems of various hierarchical levels. The paper presents the main types of machine learning, provides examples of the use of teaching methods with and without a teacher in the context of tasks related to ensuring economic security. The article presents the main algorithms of machine learning models and possible options for their use in problems of economic security. In conclusion, it is concluded that the use of machine learning tools in the analysis and forecasting of economic security in conjunction with traditional methods will allow us to give a more comprehensive assessment of the phenomena occurring.