Predicament and Thinking of College Students’ Employment and Entrepreneurship under the Background of Supply-Side Reform

Based on the analysis of the current employment and entrepreneurship of college students based on the supply-side structural reform, the employment and entrepreneurship guidance of college students is far from meeting the needs of the society. Therefore, the innovation of talent training mode needs to become an important goal of college development at this stage. Based on the previously mentioned background, this paper included 853 university students as research objects and their data from 2010 to 2018. First, we used the BP neural network as the starting point to conduct in-depth research, selected the sequential model algorithm based on the Keras framework, built a one-layer network and six types of eigenvalue labels to predict the development direction of college students’ employment and entrepreneurship, and evaluated the prediction accuracy of the model. This proves that the prediction effect of the model has the value of continuing in-depth research, and then, the prediction model is further optimized. Then, we added a three-layer network to the model and an SGD optimizer and used Softmax as the regression function to verify that the optimized model predicts well. The average accuracy of the prediction model constructed in this paper is 81.48%, the standard deviation is 4.34%, the Acc value of the model is stable at around 0.835, and the loss value is stable at around 0.3, which proves that the prediction model has a good prediction. It provides a set of application models that can be used for reference for the combination of BP neural network related knowledge and college students’ employment and entrepreneurship development direction prediction. Based on the background of the supply-side structural reform, this paper mainly analyzes and researches the current employment and entrepreneurial paths of college students in my country, hoping to provide reference for the cultivation of talents in colleges and universities.