o Linear regression and logistic regression, o Decision trees, Random Forest, Gradient Boosting (XGBoost, LightGBM, CatBoost), o Support Vector Machines (SVMs) and kernel methods, o Neural networks CNNs, RNNs, LSTMs, and Transformers, o Classification, regression, and ranking problems, o Cross-validation, bias-variance trade-off, regularization (L1/L2, dropout). Lead spec-first development initiatives using GitHub Spec Kit authoring specs, technical plans, and agent-ready task breakdowns before writing any code.