Abstract
This paper adopts a deep learning approach to analyze and study the mechanism of quantitative enhancement of college students’ employment and entrepreneurial abilities in the context of the digital era. The deep learning connotation is predetermined as five abilities, which are metacognitive ability, active communication and cooperation ability, deep processing ability, creative practice ability, and learning empathy experience, and, based on this, the deep learning questionnaire is designed, and it is reclassified by exploratory factor analysis to reduce the dimensionality, and the specific indicators and scientific connotation dimensions of the deep learning questionnaire are determined; and, through the deep learning of each dimension, the problems of deep learning of college students are examined and in-depth analysis is conducted, and the inner relationship and correlation among the dimensions of deep learning of college students are derived through correlation analysis. The success of innovation and entrepreneurship depends on the innovation and entrepreneurial ability of college students, and the formation of the ability influenced various factors. Therefore, not only is studying the influencing factors of college students’ innovation and entrepreneurship ability in line with the requirements of the times and social development, but also it can solve real problems. This thesis adopts a combination of two methods, qualitative research and quantitative research, to study the influencing factors of college students’ innovation and entrepreneurship ability and tries to ensure the scientificity, accuracy, and comprehensiveness of the conclusion. In this paper, we analyzed the requirements of the employment prediction system for graduating secondary school students, carried out the software framework and database design of the employment analysis and prediction system for secondary school students, and designed the system modularly based on the analysis results. By applying the proposed deep feedforward neural network prediction model to the prediction system, a software system applicable to the employment prediction and guidance of secondary school students is implemented.
Highlights
In today’s global economic system which is constantly developing and changing, whoever has the most innovative technology and the most innovative talents will have the first opportunity, and countries all over the world have launched the innovation-driven development strategy. erefore, it is crucial to study the factors affecting the success of college students’ entrepreneurship, and the ability of college students is the key that directly determines the success of their entrepreneurship, so it is crucial to study the ability of college students’ entrepreneurship
As the future force of social development, the improvement of the entrepreneurial ability of college students is related to the implementation of China’s innovative country construction plan and the speed of implementation [1]. erefore, it is an effective way to solve the difficulties of entrepreneurship, the low success rate of entrepreneurship, and the pressure of social employment for college students by studying the factors influencing the entrepreneurial ability of college students and exploring the strategies to improve the it in three levels [2]. erefore, the dataset needs to be segmented, and the model parameters are Scientific Programming continuously adjusted through the verification set to allow the model to converge in a better direction
We make full use of the combination of qualitative and quantitative research methods, especially through in-depth interviews with college student entrepreneurs, to summarize and analyze the factors influencing the entrepreneurial ability of college student entrepreneurs and adopt questionnaire research to supplement the model of the previous qualitative research
Summary
In today’s global economic system which is constantly developing and changing, whoever has the most innovative technology and the most innovative talents will have the first opportunity, and countries all over the world have launched the innovation-driven development strategy. erefore, it is crucial to study the factors affecting the success of college students’ entrepreneurship, and the ability of college students is the key that directly determines the success of their entrepreneurship, so it is crucial to study the ability of college students’ entrepreneurship. E employment situation of graduates from secondary colleges and universities is studied from various angles, and the problems and shortcomings of graduates in the employment process are summarized and analyzed through the analysis and tracking of the employment situation, to reflect on whether the current teaching methods and teaching priorities of secondary colleges and universities can provide students with good employment guidance and employment assistance and whether the current teaching model can cultivate excellent graduates who meet the needs of the country and society, to come up with conclusions that are conducive to adjusting the direction of career guidance and improving the quality of teaching in secondary institutions [5] From this grid form, we can clearly see the result that these parameters can be combined. A very important reason for this phenomenon is that college students do not receive good guidance during their school years, do not have a very clear career plan, and spend all day getting by, which eventually leads to employment failure. erefore, early warning and guidance for school students are a proven solution to this phenomenon
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