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