The Framingham Heart Study was a turning point in identifying the risk factors of heart disease, and is one of the most important epidemiological studies conducted. I attempt to build a decision tree classifier in Python that can predict the ten year risk of a patient developing CHD, given certain risk factors. Link to this notebook Dataset Source

The number of people who quit is critical to a company’s success. Employees are an important part of any business, so having a high turnover rate could be dangerous. Understanding what motivates people can help organisations save money by retaining key employees. Link to dashboard Dataset Source

With independent variables such as gender, tenure, and opt-in business services such as phone lines and internet services, the goal is to accurately identify customers who may churn. Customer retention and revenue generated from retention, re-subscription, and even cross-selling revenues contribute to the total customer lifetime value, which can be measured (LTV). The system’s success could be measured by examining the model’s accuracy in predicting whether or not a customer will churn.