26-28 November, 2019, Vilnius
Conference Starts in:
Sonya Liberman leads the Personalization team @ Outbrain’s Recommendations group, developing large-scale machine learning algorithms for Outbrain’s content recommendations platform serving tens of billions real-time recommendations a day. She specializes in Information Retrieval, Machine Learning, and Computational Linguistics. Before joining Outbrain, she led the Research and Algorithms @ ConvertMedia (acquired by Taboola). She holds an MSc in Computer Science and a BSc in Computer Science and Computational Biology.
From Spark to Elasticsearch and Back - Learning Large Scale Models for Content Recommendation
Serving tens of billions of personalized recommendations a day under a latency of 30 milliseconds is a challenge. In this talk I’ll share our algorithmic architecture, including its Spark-based offline layer, and its Elasticsearch-based serving layer, that enable running complex models under difficult scale constrains and shorten the cycle between research and production.