Presented By
O’Reilly + Cloudera
Make Data Work
29 April–2 May 2019
London, UK
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Augment your recommender system with transfer learning on images (sponsored by Dataiku)

Larry Orimoloye (Dataiku)
14:5515:35 Wednesday, 1 May 2019
Location: Capital Suite 2/3
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What you'll learn

  • Learn how Dataiku helped vacation retailer Voyage Privé improve its recommender systems


Recommender systems offer personalized content based on past behavior, which hooks the customer and keeps them coming back. Larry Orimoloye explains how Dataiku helped Voyage Privé, one of the world’s leading ecommerce vacation retailers, drive customers toward better recommendations. The solution uses relevant images to augment existing data, such as product pages previously visited by users, to improve the performance of the recommender systems. The new system was able to create a better-personalized experience to users in terms of what to display, which also lead to 7% increase in value per member.

This session is sponsored by Dataiku.

Photo of Larry Orimoloye

Larry Orimoloye


Larry Orimoloye is a solutions architect at Dataiku. He’s interested in driving tangible business value by combining advanced analytics using structured and unstructured data across all industries and enjoys bridging the gap between academic research and industry. He helps clients deliver ROI utilizing a business-led, technology-enabled approach to analytics; in particular, he has helped clients establish centers of excellence with an analytics remit across the organization and designed and implemented customer-centric real-time decision platforms using a combination of statistics, big data, and machine learning techniques. He holds a master’s degree in applied statistics and data mining from the University of St. Andrews.