The method of building an intelligent system of recommendations for professional orientation

Abstract

This article examines the development of intelligent systems for professional orientation through machine learning and intelligent algorithms. It explores the design features, analyzes current methods, and integrates new approaches like psychological testing, counseling, skill profiling, and job fairs with modern platforms such as social media and virtual reality. The study investigates the use of machine learning for labor market analysis, recommendation systems, and individualized learning plans, highlighting the enhanced efficiency and personalization in career guidance. The findings reveal the significant potential of these systems to refine the precision and effectiveness of career choices.