This repository compiles common machine learning interview questions covering fundamental concepts like loss functions, evaluation metrics (AUC, precision, recall, F1), model selection, overfitting/underfitting, and classical ML topics including feature engineering. It serves as a study guide and preparation resource for candidates interviewing for ML engineering roles.