01ML Fundamentals for InterviewsComplete roadmap for mastering the 12 core ML concepts tested in AI/ML interviews - bias-variance, loss functions, regularization, optimization, evaluation metrics, and more.02Bias-Variance TradeoffMaster the bias-variance tradeoff with mathematical derivations, visual intuition, and interview-ready explanations - the foundational concept behind every model selection decision.03Loss FunctionsMaster every loss function tested in ML interviews - MSE, MAE, Huber, cross-entropy, hinge, focal, contrastive, and triplet loss - with derivations, gradient analysis, and custom loss design.04Regularization TechniquesMaster every regularization technique for ML interviews - L1, L2, elastic net, dropout, batch norm, early stopping, data augmentation, and weight decay - with mathematical derivations and geometric intuition.05Optimization AlgorithmsSGD, Adam, learning rate schedules, convergence theory - mastering optimizer behavior for ML interviews.06Evaluation MetricsPrecision, recall, F1, AUC-ROC, NDCG, BLEU, perplexity - choosing the right metric for every ML problem type.07Feature EngineeringNumerical transforms, categorical encoding, text features, feature selection, and production feature stores - the art and science of feature design.08Ensemble MethodsBagging, boosting, stacking, random forests, XGBoost, LightGBM, CatBoost - understanding when and why ensembles dominate.09Cross-Validation StrategiesK-fold, stratified, time-series splits, nested CV, and group k-fold - proper validation for reliable model evaluation in interviews and production.10Handling Imbalanced DataSMOTE, class weights, focal loss, threshold tuning, and cost-sensitive learning - mastering imbalanced classification for interviews and production.11Dimensionality ReductionPCA, t-SNE, UMAP, autoencoders, and feature selection - reducing dimensions while preserving signal for interviews and production.12Probabilistic MLBayes theorem, MLE vs MAP, naive Bayes, Gaussian processes, Bayesian neural networks, and uncertainty quantification for interviews and production.13ML Interview Questions Bank50+ ML fundamentals interview questions with model answers, organized by difficulty - screening, technical deep dive, and senior/staff level.
