📊 A comprehensive comparison of TabNet and XGBoost across binary classification, multiclass classification, and regression tasks, showcasing performance metrics and fine-tuning results.

Employ the Spain's European Health Survey to predict risk of depression/anxiety

PLAYER RATING ANALYSIS

Data science project predicting SuperStore sales with Linear Regression and XGBoost. Uses date-based, engineered (discount, competitor price), and encoded categorical features. Includes preprocessing, MSE evaluation, and visualizations. Part of #60DaysOfLearning2025.

Timeseries analysis - Study case of a small business using ARIMA,SARIMA and XGBoost models to predict stock based on sales.

Classifying whether an asteroid is hazardous or not.

A loan default payment model

Short analysis of the UCI heart disease analysis, as well as walking through building a predictive model gradient boosted regression model.

📊 Predicting telecom customer churn to enable targeted retention campaigns — XGBoost & feature engineering.