An Algorithm for College Students' Employment Tendency Based on Machine Learning in a Big Data Environment

The employment difficulty of college students has become a hot topic of public concern, and the research on the employment tendency of college students is a topic that needs to be discussed in depth in the academic circle at this stage. Faced with a large number of student employment information, big data technology can be used to quickly process it. Therefore, this article takes college students from a certain university as the research object and analyzes the employment tendency of college students based on machine learning. It is found that a total of 79.67% of college students tend to work in enterprises. The number of boys willing to work in the provincial capital and above cities, small and medium cities, rural areas and other areas accounted for 32.31 %, 16.24%, and 3.09%, respectively, while the number of girls willing to work was 23.67%, 19.41
^%
, and 5.28%, respectively. University students' expectations for employment the number of people willing to earn a monthly salary of 3500–5000 yuan is the largest. Based on these data, we will analyze the student's tendency towards employment unit, employment area, and employment salary.