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This project aims to predict the final grades (G2 and G3) of students based on various factors such as age, study time, family support, and more.It utilizes machine learning techniques to make predictions and offers insights into the factors affecting students' grades.
Jupyter Notebook associated with our submission for the 2023 ICASSP, "Sensor Selection for Angle of Arrival Estimation Based on the Two-Target Cramér-Rao Bound"
Cavities collection and similarity map of the binding sites on SARS-CoV-2, SARS-CoV and MERS-CoV targets providing all 3D protein structures, cavities, ligands and interactors