Research on the prediction model of employment destination of college graduates based on deep learning

With the continuous growth of the number of college graduates, the employment problem has become a focus of social attention. In order to overcome this problem, this paper constructs a model for predicting the employment destination of college graduates based on deep learning. The model integrates multi-dimensional data such as demographic characteristics, academic achievements, and psychological activities, and also combines government governance indicators, such as the evaluation score of regional employment resources and the proportion of government public positions to make predictions. The experimental results show that the proposed model has high accuracy and strong generalization ability in the prediction of six employment categories. Compared with traditional machine learning methods, the improvement is very significant. Visual analysis is carried out with the help of confusion matrix, prediction probability distribution map, etc., which further proves the classification performance of the model and the potential value of its application. The research results of this paper provide practical technical support for the employment guidance of college graduates, the formulation of government employment policies, and the recruitment of corporate talents, reflecting key theoretical and practical significance.