McGill AI Podcast
There are very few places in the world like Montreal and McGill which have such a concentration of talent in the field of AI/ML. MAIS primarily serves to build a community with a shared passion for the field, spreading knowledge and resources to help aid people trying to enter the AI ecosystem. Our podcast aims to promote the research and share the experiences of people who are making remarkable contributions to the development of AI across disciplines and to allow others to use that information to break into the field while being more aware of the challenges and opportunities. We hope to foster an accessible, holistic resource to understand how AI is evolving and continuously changing the world around us.
McGill AI Podcast
Dan Cervone: Machine Learning in Sports
Dr. Dan Cervone is the principal data scientist at Zelus Analytics where they are building the world leading sports analytics platform. Prior to this, Dan spent three seasons with the Los Angeles Dodgers, most recently as Director of Quantitative Research. He completed his PhD in Statistics at Harvard University, and was then a Moore-Sloan Data Science Fellow at NYU. His work focuses on spatiotemporal data and hierarchical models, with particular application to sports analytics and player tracking data. Dan joins us today to talk about the field of sports analytics, his own research using machine learning in sports, and the future of sports analytics.
Music by Aria Khiabani with other music under the name SATRAP
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