Diversification in Recommender Systems with Ahsan Ashraf

800 800 This Week in Machine Learning & AI

In this episode of our Strata Data conference series, we’re joined by Ahsan Ashraf, data scientist at Pinterest.

In our conversation, Ahsan and I discuss his presentation from the conference, “Diversification in recommender systems: Using topical variety to increase user satisfaction.” We cover the experiments his team ran to explore the impact of diversification in user’s boards, the methodology his team used to incorporate variety into the Pinterest recommendation system, the metrics they monitored through the process, and how they performed sensitivity sanity testing.

Thanks to our Sponsors!

Thanks to Cloudera and Capital One for their continued support of the podcast and their sponsorship of this series.

Cloudera’s modern platform for machine learning and analytics, optimized for the cloud, lets you build and deploy AI solutions at scale, efficiently and securely, anywhere you want. In addition, Cloudera Fast Forward Lab’s expert guidance helps you realize your AI future, faster. To learn more, visit Cloudera’s Machine Learning resource center at cloudera.com/ml.

At the NIPS Conference in Montreal this December, researchers from Capital One will be co-hosting a workshop focused on Challenges and Opportunities for AI in Financial Services and the Impact of Fairness, Explainability, Accuracy, and Privacy. A call for papers is open now through October 25, for more information or submissions, visit twimlai.com/c1nips. A limited number of full NIPS Conference tickets are also available for accepted speakers (one full-price ticket only, applied directly to the accepted speaker),and will be made available along with author notifications on Oct 29, 2018.

About Ahsan

Mentioned in the Interview

“More On That Later” by Lee Rosevere licensed under CC By 4.0

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