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Abstract
The object of research is the process of developing a predictive model for assessing the performance of university students based on the results of current studies. The purpose of the study is to build a predictive model of students' session results depending on the estimated parameters of current performance. The main problems in this area were analyzed, and goals were set for their direct implementation, fragmented preliminary data processing to build a machine learning model. Various machine learning models were built and the qualitative indicators of each model were evaluated. After selecting the optimal model, a graphical user interface for the predictive model was created. A predictive model of university students academic performance was created, as well as a graphical interface for its use. The significant factors in predicting student performance have been identified.
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