This project is based on a case study that focuses on Employee Attrition. The data is taken from IBM Watson's sample case study data. I have utilized data mining and basic machine learning algorithms to predict the Employee Attrition of a pharmaceutical company.
For this classification use case, I have used different machine learning models like
- Boosted Decision Trees,
- Logistic Regression,
- Decision Forests,
- Neural Networks and
- Naive Bayes.
I also found out important predictors or factors that could help predict the possible attrition. I have used Tableau for visualizations to showcase the correlation between the top predictors with the target variable of Attrition. I have used Microsoft Azure Machine Learning Studio for the machine learning model development.
One of the most important resource for successful functioning of any organization or company is the People resource. Hence, losing the right people from the company can be a huge setback. Thus, understanding the factors or reasons for attrition makes it, all the more, necessary for a company or organization.