Smart Result Analysis System Using Machine Learning

Educational institutions generate a large amount of student performance data every semester. Traditional result analysis methods are mostly manual and time-consuming, making it difficult for faculty members to identify patterns and improve academic performance. This paper proposes a Smart Result Analysis System using Machine Learning that automates the analysis of student results and predicts academic performance. The system uses machine learning algorithms to analyse student marks, identify weak and strong learners, and generate statistical reports. The proposed system helps teachers understand performance trends, improve teaching strategies, and support slow learners. Experimental results show that the system provides efficient and accurate result analysis compared to manual methods.