Data Cleaning & Classification

Developed an end-to-end machine learning pipeline for preparing and classifying real-world data. I handled data preprocessing, duplicate and missing-value treatment, outlier detection, skewness analysis, feature selection, categorical encoding, and train-test splitting. I then trained and evaluated Logistic Regression and K-Nearest Neighbors models to build a reliable classification solution and understand how data quality and feature preparation affect model performance.