Project from the subject ML of the MIRI.
Authors: Miguel Hernandez and Jaume Pladevall.
We used machine learning methods to predict student success according to the information retrieved about them and also find which are the most important features that affect the student performance.
We worked with the data provided by Cortez and Silva and retrieved from the UCI Machine Learning Repository.
P. Cortez and A. Silva. Using Data Mining to Predict Secondary School Student Performance. In A. Brito and J. Teixeira Eds., Proceedings of 5th FUture BUsiness TEChnology Conference (FUBUTEC 2008) pp. 5-12, Porto, Portugal, April, 2008, EUROSIS, ISBN 978-9077381-39-7. http://www3.dsi.uminho.pt/pcortez/student.pdf
The code can be found in the Project_code jupyter notebook.