The podcast you’re about to hear is the first of a handful of interviews I recorded live from the O’Reilly AI and Strata conferences in New York City.
My first guest in this series is Carlos Guestrin, the Amazon professor of Machine Learning at the University of Washington. You may recall my discussion of Carlos’ company Turi being recently acquired by Apple.
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Earlier this year, Carlos and one of his PhD students, Marco Ribeiro, and Sameer Singh, then a postdoc at UW, published some very interesting research into explaining the predictions of machine learning algorithms. Their paper, titled, “Why Should I Trust You?: Explaining the Predictions of Any Classifier,” has been on my reading list for a while, and discussing this work was the main focus of my conversation with Carlos.
About Carlos Guestrin
Mentioned in the Interview
- Carlos’ Machine Learning Course Sequence on Coursera
- [1602.04938] “Why Should I Trust You?”: Explaining the Predictions of Any Classifier
- LIME – Local Interpretable Model-Agnostic Explanations
- GitHub – marcotcr/lime: Lime: Explaining the predictions of any machine learning classifier
Image Credit: John Vicory/Seattle Business