data-mining

• Conducted exploratory data analysis, built and evaluated supervised learning models: Linear/Logistic Regression, Naive Bayes, KNN
• Implemented feature selection methods (Backward Elimination, Forward Selection, Lasso/Ridge Regularization) to optimize model performance
• Applied statistical hypothesis testing (Wald test, t-test) to evaluate feature significance and model quality
• Solved practical problems: body fat prediction, binary classification, and product placement optimization