Student Performance Evaluation Based on Machine Learning

Abstract: This project is a Flask-based web application developed to automate the evaluation of student performance across various technical domains. It allows users to upload text or image-based content (presumably representing course submissions or project work), which is then analyzed using a backend machine learning model implemented in Python (model.py). The application provides a user-friendly interface for input through HTML templates and produces evaluative results in real time. Supporting features include integration of static media resources and structured course categorization (e.g., AI, Python, IoT). The goal is to streamline the assessment process by leveraging intelligent algorithms for quick and accurate evaluations.

Keywords: Student Evaluation Automated Grading