Construction of Big Data-Driven Students’ Career Planning and Innovation and Entrepreneurship Education Path by Integrating Support Vector Machine Algorithm

This study aims to construct an effective pathway for students' career planning and innovative industry education by integrating support vector machine algorithm with big data analysis technology.By effectively integrating multi-source data and combining the improved genetic algorithm for feature selection and extraction of student data, the support vector machine algorithm is used to conduct indepth analysis of the data related to students' career planning and innovation and entrepreneurship education, to provide students with accurate and personalized career and entrepreneurship guidance, and based on which, the career planning and innovation and entrepreneurship education path is constructed.Experimental analysis of the classification prediction performance of the support vector machine algorithm and comparison with other classification prediction algorithms show that the support vector machine algorithm used in this paper has the highest classification accuracy in the assessment of students' career planning and innovation and entrepreneurship ability, and the model performance is the most stable.The results of the educational experiment show that after using the educational path proposed in this paper, the students' satisfaction with career planning and the mean value of the assessment score of innovation and entrepreneurship ability increase by 70.89% and 170.73%, respectively.The above results fully demonstrate the effectiveness of the educational path constructed in this paper, which provides a useful reference for efficient education and teaching reform.