Yelp Ad Targeting at Scale with Apache Spark

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From training billions of ad impressions to scaling gradient boosted trees with more than three million nodes, Ad Targeting at Yelp uses Apache Spark in many stages of its large-scale machine learning pipeline.
This session will explore examples of how Yelp employed and tweaked Spark to support big data feature engineering, visualizations and machine learning model training, evaluation and diagnostics. You’ll also hear about the challenges in building and deploying such a large-scale intelligent system in a production environment.

Session hashtag: #SFml7

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About Joe Malicki

Joe has over 16 years experience in technology, building systems from compilers, streaming media engines, distributed systems, and search engines for, natural language understanding in finance, and now works at Yelp building machine learning for Ad Targeting.

About Inaz Alaei-Novin

Inaz is originally from Iran. She did her M.A.Sc at The University of Toronto in Canada, and worked there for a year at Modiface. Currently she works as a data mining engineer at Yelp.