Speaker: Sean Downes, Sr. Data Scientist, Expedia
Presentation: For technology companies, there is an inherent tension between streaming and batch processing. Real-time data streams can transform a small input signal into an immediate response, but machine learning is most effective in batch. Modern data platforms can easily handle both streaming and batch jobs simultaneously. Balancing these two paradigms thus becomes a matter of design, and right now this interplay is thriving at the intersection of product and data science. We discuss these dualities in the context of recommendations systems, some of our core products at Expedia. We’ll sketch the design, architecture, tools, and metrics, as well as share our experience with our attempts at personalization. We’ll merge the ideas behind multi-armed bandits and learning-to-rank to develop a novel recommendation system and give you the background needed to start building products in this rapidly evolving space.
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