Adult Income Classification using Machine Learning

Developed a Machine Learning model to predict whether an individual's income exceeds $50K per year based on demographic and work-related features.

Performed data preprocessing including handling missing values, encoding categorical variables, and feature scaling.

Trained and evaluated classification models to achieve accurate predictions, using performance metrics such as accuracy, precision, and recall.

Built the project using Python and key libraries such as Pandas, NumPy, and Scikit-learn.