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The applications data was analyzed for the purpose of developing a supervised identity fraud detection model to identify candidates for fraudulent applications. To build this model, the fraud label was assessed in relation to the linkage of five personally identifiable parameters which include SSN, address, phone number, date of birth and zip co…
This project contains 5 advanced SQL queries implemented in 5 different ways; 4 of them are based on R and its frameworks, and one of them is Python based.
Dementia-related deaths in Europe, focusing on gender-based trends. Utilized R to create 10 visualizations exploring data from 2011-2020, specifically focusing on Greece.
Evaluate the purchase data of 594 households in Philadelphia (total 9781 purchases) and propose a forecasting model for the purchase rates of various SKUs.