The project is based on analyzing a non-profit organization's donor database and provide recommendations on improving fundraising strategies. The study also explores
on building machine learning models to predict donation scores. The project presents an opportunity for the non-profit to make the most out of their
data and improve fundraising efforts, ultimately allowing them to better serve the children and families they support.
The project aims to showcase the disparity factors that affect women.
The three main dimensions that reflect the
Gender Inequality Index - reproductive health, empowerment, and the labor market, are visualized in this project.
Analyis of domestic USA airlines, extracted raw data, normalized and created dependency diagrams
Loaded to MySQL, analysed the trends with queries and created interactive visualizations for three time periods
including peak COVID pandemic flight data.
The study attempts to find the significant medical factors that play a role in a patient's death due to heart failure.
The goal of this research will be to make use of tree-based models and support vector machines to predict patients’ survival event.