This project uses the given attendence and absence data of the various employee and training program. The goal is to implement models that will help us access the likely hood of an employee attending a training session. This will help improve the curriculumn of training sessions that are not attended as often, reallocate budget, and make changes to the adverstisement strategy.
The data set has been provided by the HR Department. It consists of data from 2018 and 2019 and includes categorical information of the employee and the training program and whether they dropped out or not.
The project is split into sections: cleaning the dataset, exploratory analysis, prediction model, and model testing.