This project aims to predict customer conversion for an insurance company. Using historical data, we will develop a machine learning model that can identify which customers are most likely to purchase a policy. By understanding the patterns and behaviors of previous customers, the model can make predictions and provide valuable insight to company.

The objective of the project is to diagnostically predict whether or not a patient has diabetes, based on certain diagnostic measurements included in the dataset. Several constraints were placed on the selection of these instances from a larger database. In particular, all patients here are females at least 21 years old of Pima Indian heritage.