Research on Intelligent Recommendation Algorithm Model for Vocational Talent Training

This paper proposes a vocational talent training model based on intelligent recommendation algorithm. By integrating the personal characteristics, interests, hobbies, career potential and other data of students, intelligent recommendation technology is used to provide students with personalized course recommendations, career path planning and job matching. Advanced algorithms such as collaborative filtering, deep learning and reinforcement learning are used in the study to construct a recommendation model that adapts to the needs of different students. The experimental results show that the vocational talent training system based on intelligent recommendation has significant improvements in recommendation accuracy, student satisfaction and course matching efficiency. The accuracy of course recommendations has increased by 18%, the student satisfaction with personalized recommendations has increased by 25%, and the accuracy of the system's career path planning has reached more than 90%. Through in-depth analysis of experimental data, this paper verifies the application value of intelligent recommendation technology in vocational talent training, and proves its advantages in improving educational effects, optimizing student training paths and enhancing career matching.