A Comparative Analysis of Machine Learning Algorithms to Predict Academic Performance using KDD methodology
Repository of Individual Project (SID:10002997)
This repository contains the dataset, files and code used for my Computer Science with Artificial Intelligence dissertation. The aim of this project was to answer the following questions:
-
How accurately can different machine learning algorithms predict academic performance in higher education?
-
To what extend does different student features influence academic performance predictions?
- Philbert Baby- Project Manager
- Aram Saeed - Supervisor
To run the .ipynb code file, please download the following software:
To set up the working environment on Jupyter notebook, please download the following libraries :
!pip install pandas numpy matplotlib seaborn plotly
!pip install tensorflow keras livelossplot scikit-learn Pillow
!pip install openpyxl
!pip install xgboost
- Coventry University - Dissertation submitted on behalf of this Univeristy.
- Universidad Tecnologica de Bolivar - Obtained the Dataset from this University.
- Enrique De La Hoz - Developed the dataset used in this research.