Postgraduate Development Dynamic Early Warning of Improved Deep Learning Algorithms

With the development of society and the in-depth advancement of higher education, postgraduates are facing increasing pressures in education, economy, work and psychology. To ensure the teaching quality of postgraduates and improve the development level of postgraduates, it is necessary to pay attention to their academic dynamics, and the academic development dynamics of postgraduates includes not only academic performance, but also the ability to take care of themselves. Whether there are deviations in study or life, the quality of postgraduate teaching will be greatly reduced. Therefore, this paper establishes a postgraduate early warning standard to supervise and manage the students' performance in the whole process, and uses the improved deep learning algorithm to analyze the students' academic credits, failed courses, skill certificates, and dormitory hygiene and psychological conditions in life. Health conditions and other related early warning data to obtain students' comprehensive credit scores, and analyze whether to make early warning management of students corresponding to the early warning signals.