The Math Behind Recommender Systems

Video Description

How do Netflix, YouTube, and other platforms predict what you'll watch next? Dive into the fascinating world of recommender systems (Content Filtering vs Collaborative Filtering) and the mathematics behind your personalized recommendations. In this video, we explore: - Content Filtering vs Collaborative Filtering - The Netflix Prize Problem - Matrix Factorization explained simply - How patterns in user behavior predict preferences - Real-world applications beyond movies Perfect for students and professionals interested in: - Machine Learning - Data Science - AI Systems - Software Engineering - Recommendation Algorithms Original Research Paper: "Matrix Factorization Techniques for Recommender Systems" https://www.inf.unibz.it/~ricci/ISR/papers/ieeecomputer.pdf Key Timestamps: 0:00 The Netflix Prize Problem 2:06 Content Filtering Explained 4:36 Collaborative Filtering Approach 5:26 Matrix Factorization #MachineLearning Paper in this video: Matrix Factorization Techniques for Recommender Systems https://www.inf.unibz.it/~ricci/ISR/papers/ieeecomputer.pdf