SlideShare a Scribd company logo
1 of 42
▪
▪
▪
▪
▪
▪
▪
▪
▪
▪
▪
▪
▪
▪
▪
▪ …
▪ …
▪
▪ …
▪
▪
▪
▪
▪
▪
▪
US
FR
US
FR
1,000 users
100 users
0
...
...Co-occurrences
R ≈ UM
US
FR
1,000 users
100 users
100,000 users
10 users
≈
US
FR
2016-01-01 2016-01-02
Newly available
▪
▪
▪
▪
▪
▪
▪
▪
▪
▪
▪
▪
▪
▪
▪
▪
▪
▪
≈+
US US/AU FR
?
▪
▪
▪
▪
▪
▪ …
Recommending for the World

More Related Content

More from Justin Basilico

Artwork Personalization at Netflix
Artwork Personalization at NetflixArtwork Personalization at Netflix
Artwork Personalization at Netflix
Justin Basilico
 

More from Justin Basilico (12)

Recent Trends in Personalization at Netflix
Recent Trends in Personalization at NetflixRecent Trends in Personalization at Netflix
Recent Trends in Personalization at Netflix
 
Recap: Designing a more Efficient Estimator for Off-policy Evaluation in Band...
Recap: Designing a more Efficient Estimator for Off-policy Evaluation in Band...Recap: Designing a more Efficient Estimator for Off-policy Evaluation in Band...
Recap: Designing a more Efficient Estimator for Off-policy Evaluation in Band...
 
Recent Trends in Personalization: A Netflix Perspective
Recent Trends in Personalization: A Netflix PerspectiveRecent Trends in Personalization: A Netflix Perspective
Recent Trends in Personalization: A Netflix Perspective
 
Artwork Personalization at Netflix
Artwork Personalization at NetflixArtwork Personalization at Netflix
Artwork Personalization at Netflix
 
Deep Learning for Recommender Systems
Deep Learning for Recommender SystemsDeep Learning for Recommender Systems
Deep Learning for Recommender Systems
 
Making Netflix Machine Learning Algorithms Reliable
Making Netflix Machine Learning Algorithms ReliableMaking Netflix Machine Learning Algorithms Reliable
Making Netflix Machine Learning Algorithms Reliable
 
Déjà Vu: The Importance of Time and Causality in Recommender Systems
Déjà Vu: The Importance of Time and Causality in Recommender SystemsDéjà Vu: The Importance of Time and Causality in Recommender Systems
Déjà Vu: The Importance of Time and Causality in Recommender Systems
 
Recommendations for Building Machine Learning Software
Recommendations for Building Machine Learning SoftwareRecommendations for Building Machine Learning Software
Recommendations for Building Machine Learning Software
 
Recommendations for Building Machine Learning Software
Recommendations for Building Machine Learning SoftwareRecommendations for Building Machine Learning Software
Recommendations for Building Machine Learning Software
 
Learning to Personalize
Learning to PersonalizeLearning to Personalize
Learning to Personalize
 
Learning a Personalized Homepage
Learning a Personalized HomepageLearning a Personalized Homepage
Learning a Personalized Homepage
 
Recommendation at Netflix Scale
Recommendation at Netflix ScaleRecommendation at Netflix Scale
Recommendation at Netflix Scale