Advanced Algorithms

• Deep dive into matrix factorization techniques (SVD, ALS)
• Introduction to neural network-based recommenders (autoencoders, CNNs for recommendation)

Evaluation and Optimization

• Cross-validation techniques for recommender systems
• Overfitting prevention strategies
• Parameter tuning (grid search, random search)

Context-Aware Recommender Systems

• Incorporating context into recommendations (time, location, device)
• Algorithmic adjustments for context-awareness

Ensemble Techniques

• Combining multiple models for improved performance
• Stacking, blending, and boosting applied to recommender systems

Case Study Discussion