Project Overview
This project involved analyzing the Current Population Survey dataset and applying data cleansing techniques and descriptive statistics to identify trends and insights. A predictive model was built using linear regression, XGBoost, and Random Forest algorithms, achieving 85% accuracy in predicting net family income. I worked on over 51 variables for prediction. The findings were effectively communicated through visually appealing data visualizations, showcasing strong analytical and communication skills. The project provided valuable insights into demographic and socioeconomic factors influencing net family income.
