loopiiu / dsp2_endterm

Expresso Churn Prediction Challenge - dealing with imbalanced dataset

Data Science Programming 2 Endterm

About the dataset

Context

This data was imported from the zindi platform in the context of competition and here is the link to the competition.
The objective of the competition is to develop a predictive model that determines the likelihood for a customer to churn - to stop purchasing airtime and data from Expresso.
Dataset was taken from Kaggle.
Here is the link link

In the notebook section you can find 2 notebook files.

• The first notebook consists of applying different classification model with our datasets, along with the data cleaning.
• The second notebook is all about EDA.