This project was a major part of a course I took - "Introduction to Machine Learning" at TAU's faculty of engineering in 2024, during the 2nd year of my studies.
The project is about a classification problem for a telecom company, with a given dataset. In a sentence - along with my 2 partners, we ran multiple ML models in order to predict subscription to a plan. Furthermore, we visualized the data, handled outliers & missing values, evaluated the models' performances, etc. We had the data split into a training set & a test set. We evaluated the model's performance using the AUC (Area Under Curve) metric, on the training set, and the model with the best AUC was chosen to make predictions on the test set.
The full details can be found in the notebook file (IPYNB) and in the Final Report (PDF), in the repo, written in Hebrew.
The project's final grade - 100.