Recommender Systems: Evaluation Metrics and Ethical Challenges [Episode-38]

How do Netflix, YouTube, Spotify, and Amazon know what you'll like next? In this episode, explore the fundamentals of AI recommender systems, including content-based filtering, collaborative filtering, hybrid recommendation models, and the cold start problem. Learn how modern AI techniques like Graph Neural Networks (GNNs) and Recurrent Neural Networks (RNNs) improve recommendations while addressing ethical concerns such as algorithmic bias, privacy, filter bubbles, and fairness. Discover the key evaluation metrics that measure recommendation quality beyond simple accuracy.