Justin Basilico
368
Abonné
Personal Information
Entreprise/Lieu de travail
San Francisco Bay Area United States
Profession
Research/Engineering Director at Netflix - Machine Learning and Recommendation Systems
Secteur d’activité
Technology / Software / Internet
Site Web
www.netflix.com
À propos
Leading machine learning researchers and engineers to solve hard, important problems. Balancing research, software engineering, management, and vision. Doing end-to-end machine learning: creating new ideas, designing algorithms running experiments, analyzing the data, deploying in real applications, and building next-generation machine learning infrastructure to make it seamless. Currently focused on innovating the Netflix homepage through better recommendations and personalization to increase our members joy.
Specialties: Machine Learning, Personalization, Recommender Systems, Deep Learning, Collaborative Filtering, Information Retrieval, Text Analysis, Artificial Intelligence
Mots-clés
personalization
netflix
machine learning
recommender systems
recommendations
large scale
collaborative filtering
contextual bandits
software engineering
distributed systems
page generation
metrics
reinforcement learning
deep learning
online learning
artwork personalization
causality
user experience
experience personalization
fairness
ranking
off policy evaluation
multi-task learning
multi armed bandits
failure injection
reliability
time
future
global recommendations
spark
design patterns
Tout plus
- Présentations
- Documents
- Infographies
Recent Trends in Personalization at Netflix
Justin Basilico
•
il y a 2 ans
Recap: Designing a more Efficient Estimator for Off-policy Evaluation in Bandits with Large Action Spaces
Justin Basilico
•
il y a 3 ans
Recent Trends in Personalization: A Netflix Perspective
Justin Basilico
•
il y a 3 ans
Artwork Personalization at Netflix
Justin Basilico
•
il y a 4 ans
Deep Learning for Recommender Systems
Justin Basilico
•
il y a 5 ans
Making Netflix Machine Learning Algorithms Reliable
Justin Basilico
•
il y a 5 ans
Déjà Vu: The Importance of Time and Causality in Recommender Systems
Justin Basilico
•
il y a 5 ans
Past, Present & Future of Recommender Systems: An Industry Perspective
Justin Basilico
•
il y a 6 ans
Is that a Time Machine? Some Design Patterns for Real World Machine Learning Systems
Justin Basilico
•
il y a 6 ans
Recommendations for Building Machine Learning Software
Justin Basilico
•
il y a 7 ans
Recommendations for Building Machine Learning Software
Justin Basilico
•
il y a 7 ans
Lessons Learned from Building Machine Learning Software at Netflix
Justin Basilico
•
il y a 8 ans
Personalized Page Generation for Browsing Recommendations
Justin Basilico
•
il y a 8 ans
Learning to Personalize
Justin Basilico
•
il y a 8 ans
Learning a Personalized Homepage
Justin Basilico
•
il y a 9 ans
Recommendation at Netflix Scale
Justin Basilico
•
il y a 9 ans