Xavier Amatriain

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I build awesome teams to tackle complex problems with a big business impact. Currently starting a startup in the Healthcare/AI space. I enjoy working on the cross-roads of data mining, machine learning, software engineering, innovation, and agile methods. I have 10+ years of experience in research, research management & software engineering. I have authored more than 50 papers in books, journals and international conferences. I have managed different kinds of research teams and projects: from the CLAM Open Source Framework, to the Allosphere project at UCSB. I enjoy seeing and discussing the big picture and the business impact as much as diving into all sorts of technical details. I am...

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Xavier Amatriain

10 more lessons learned from building Machine Learning systems

Recommender Systems (Machine Learning Summer School 2014 @ CMU)

10 more lessons learned from building Machine Learning systems - MLConf

10 Lessons Learned from Building Machine Learning Systems

Kdd 2014 Tutorial - the recommender problem revisited

Machine Learning to Grow the World's Knowledge

Recsys 2014 Tutorial - The Recommender Problem Revisited

Netflix Recommendations - Beyond the 5 Stars

Building Large-scale Real-world Recommender Systems - Recsys2012 tutorial

The Science and the Magic of User Feedback for Recommender Systems

Lessons learned from building practical deep learning systems

Lean DevOps - Lessons Learned from Innovation-driven Companies

Recsys 2016 tutorial: Lessons learned from building real-life recommender systems

Qcon SF 2013 - Machine Learning & Recommender Systems @ Netflix Scale

Past, present, and future of Recommender Systems: an industry perspective

Media, data, context... and the Holy Grail of User Taste Prediction

Staying Shallow & Lean in a Deep Learning World

Past present and future of Recommender Systems: an Industry Perspective

Medical advice as a Recommender System

Machine Learning for Q&A Sites: The Quora Example