Episode 44 - Ranking Foursquare Tips with Enrique Cruz
If you want to know how machine learning is used to solve real world problems (even first world problems like helping you out at restaurants) - then this episode is for you.
Max and Enrique Cruz talk about how Foursquare ranks its tips, how we used machine learning in the process, and our takeaways from how content is ranked online generally.
Links
Enrique’s paper on Foursquare Tip Ranking for the 2016 ACM Recommender Systems Conference
Enrique Cruz has been a Staff Machine Learning Engineer for Foursquare over the last 4 years. He is originally from Caracas, Venezuela and first came to New York in 2010 to obtain a degree in Computer Science from Columbia University. He's focus in the industry has been mostly within the realm of Search & Ranking. Specifically he currently specializes in building and deploying machine learning systems to to tackle various applied search and ranking problems.
Previous Episodes
Episode 43 on Self Driving Cars, which I follow up a bit on in this episode
Episode 38 with our predictions panel
Episode 23 on Natural Language Processing at Foursquare
Episode 7 with Foursquare’s Founder
Episode 3 on Foursquare’s Rating System
Episode 2 on Foursquare’s Internationalization System
