Machine Learning: How Did We Get Here?

Tom sits down with Michael I. Jordan, Director of Rearch at Inria and Professor Emeritus of the Departments of EECS and Statistics, University of California, Berkeley. Michael has been a major contributor to machine learning, especially at the intersection of statistics and machine learning.

Michael discusses his research trajectory, including how it has been inspired by ideas from control theory, statistics, and most recently economics.

Creators and Guests

Host
Tom Mitchell
Tom Mitchell is the University Founders Professor at Carnegie Mellon University, a Digital Fellow at the Stanford Digital Economy Lab, and the author of Machine Learning, a foundational textbook on the subject.
Producer
Matty Smith
Writer/director/editor from Los Angeles, with experience writing and directing scripted television and national commercials. Mixed media producer with hands-on experience in all areas of production.
MJ
Guest
Michael I. Jordan
Director of Research, Inria | Professor Emeritus, Departments of EECS and Statistics, University of California, Berkeley

What is Machine Learning: How Did We Get Here??

Tom Mitchell literally wrote the book on machine learning. In this series of candid conversations with his fellow pioneers, Tom traces the history of the field through the people who built it. Behind the tech are stories of passion, curiosity, and humanity.

Tom Mitchell is the University Founders Professor at Carnegie Mellon University, a Digital Fellow at the Stanford Digital Economy Lab, and the author of Machine Learning, a foundational textbook on the subject. This podcast is produced by the Stanford Digital Economy Lab.