AI & ML
ML Foundations
Every ML interview starts here. Master the fundamentals that separate junior from senior candidates.
Core ML Concepts
Supervised vs Unsupervised Learning
Reinforcement Learning Fundamentals
The Bias-Variance Tradeoff
Training, Validation, and Test Sets
Regression & Classification
Linear Regression Deep Dive
Logistic Regression Explained
Regularization - L1 vs L2
Tree-Based Methods
Decision Trees Fundamentals
Random Forests
Gradient Boosting & XGBoost
Model Evaluation
Classification Metrics
ROC Curves and AUC
Regression Metrics & Error Analysis