The following Video Lectures on Recommender Systems were given by Netflix Research/Engineering Director, Xavier Amatriain at Machine Learning Summer School 2014 at Carnegie Mellon University in Pittsburgh.
This is the outline of the lecture (Videos below):
- Introduction: What is a Recommender System
- “Traditional” Methods
- Collaborative Filtering
- Content-based Recommendations
- “Novel” Methods
- Learning to Rank
- Context-aware Recommendations
- Tensor Factorization
- Factorization Machines
- Deep Learning
-
Similarity
-
Social Recommendations
- Hybrid Approaches
-
A practical example: Netflix
-
Conclusions
-
References
Watch Part 1 (2hrs):
http://www.mlss2014.com / See the website for more videos and slides.
Watch Part 2 (2 hrs)
Recommender Systems (Machine Learning Summer School 2014 @ CMU) from Xavier Amatriain