Microsoft Malware Prediction – Machine Learning Project

Using telemetry data from Microsoft Defender, I developed a predictive model for malware detection. I applied

memory optimization, handled missing values and outliers, and used various data visualization techniques. By

tuning an XGBoost model with cross-validation, I achieved strong performance. The project utilized Python,

XGBoost, Pandas, and Seaborn, efficiently processing over 8 million rows.