University Admission Trend Analysis and Insight Generation System

The University Admission Trend Analysis and Insight Generation System (UAT) is a machine learningbased application designed to help students evaluate their chances of getting admission to universities. The system analyzes important academic factors such as GRE score, TOEFL score, CGPA, Statement of Purpose (SOP), Letter of Recommendation (LOR), university ranking, and research experience to predict admission possibilities. It uses historical admission data and machine learning algorithms to generate accurate predictions and useful insights. The application includes an interactive dashboard that displays admission trends and visualizations, helping students understand the factors that influence admission decisions and identify areas for improvement. Developed using Python, Streamlit, Pandas, NumPy, Scikitlearn, and Plotly, the system provides a user-friendly platform for data analysis and decision-making. By offering predictive insights and trend analysis, UAT assists students in selecting suitable universities and planning their academic goals more effectively.