Building Interpretable Models on Imbalanced Data

Predicting customer churn from a telecom provider

I’ve always believed that to truly learn data science you need to practice data science and I wanted to do this project to practice working with imbalanced classes in classification problems. This was also a perfect opportunity to start working with mlflow to help track my machine learning experiments: it allows me to track the different models I have used, the parameters I’ve trained with, and the …

building data data-sicence decision-tree imbalanced-dataset machine learning towards-data-science