Summary

The project focuses on solving four specific tasks using machine learning models:

1. **Customer Segmentation:** Identifying customers similar to a target customer, thereby assisting agents in their marketing strategies.
2. **Risk Prediction:** Calculating the probability that a new customer will receive an insurance benefit, evaluating whether a predictive model can outperform a basic (dummy) model.
3. **Benefit Estimation:** Using a linear regression model to predict the number of benefits a new customer might receive.
4. **Data Masking:** Implementing a data transformation algorithm to protect customers' personal information without compromising the quality of the machine learning models.

Github repository