Advanced Machine Learning

Topics covered

• Ensembles & recommendations: Boosting, mixture of experts, stacking, recommender systems, and ranking.
• Representations & foundation models: Spectral clustering, autoencoders, fine-tuning, and model compression.
• Privacy: Privacy attacks and differential privacy.
• Interpretability: Model explanations with LIME and SHAP.