Give Users the Wheel

Where did recommender systems come from, and how do we know when they're actually working? In part one of Data Skeptic's three-part Recommender Systems finale, Kyle traces the field from collaborative filtering and the Netflix Prize to matrix factorization and modern approaches, ...  Show more

Recommender systems influence nearly every aspect of our digital lives—but what does it mean for those systems to be fair? Robin Burke joins Data Skeptic to discuss the history of recommender systems, the limitations of optimizing purely for accuracy, and how ideas from social ch ...  Show more

In episode nine we talk with George Dahl, of  the University of Toronto, about his work on the Merck molecular activity challenge on kaggle and speech recognition. George recently successfully defended his thesis at the end of March 2015. (Congrats George!) We learn about how net ...  Show more

Podcast with Gautam Siwach and Jin Vanstee ! Speaker - Elpida Tzortzatos is an IBM Fellow and CTO AI on IBM zSystems. In this Podcast we listen to Elpida's thoughts about driving Artificial Intelligence strategies, associated risks, and Values.We will learn how to drive industry- ...  Show more

In this episode of the SuperDataScience Podcast, I chat with the President and Editor at KDNuggets, Gregory Piatetsky-Shapiro. You will hear about the recent advancements in Data Science, learn how Reinforcement Learning can greatly improve AI capabilities, and learn about the no ...  Show more

In this episode of the SuperDataScience Podcast, I chat with my friend and business partner, Hadelin de Ponteves. You will hear what new exciting things are happening in Hadelin's life now. You will hear some preview of his upcoming presentation at DataScienceGO 2019, which will ...  Show more