Question analyzer for students utilizing MongoDB and Natural Language Processsing is a creative arrangement that intends to further develop understudy learning results. The framework will use different strategies and calculations to handle a lot of information, including grades, participation records, and segment data. A potential method is the SVM algorithm found in the scikit-learn toolkit. A well-liked machine learning approach called SVM (Support Vector Machines) may be applied to classification and regression problems. A popular Python framework for machine learning called Scikit-learn offers a variety of tools for data analysis and model construction. This project aims to develop a machine learning system to analyzing academic achievement of students using machine learning approaches. The ultimate focus of the program is to assist educators and administrators in making informed decisions to enhance student performance and academic outcomes. The system will provide a powerful, data-driven tool that can help educators and administrators make informed decisions and promote better academic outcomes for students.
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