In episode thirteen of season two, we talk about t-Distributed Stochastic Neighbor Embedding (t-SNE) we take a listener question about statistical physics, plus we talk with Hal Daume of the University of Maryland. (who is a great follow on Twitter.)

Automatic Translation and t-SNE

In episode fourteen of season two, we talk about Perturb-and-MAP, we take a listener question about classic artificial intelligence ideas being used in modern machine learning, plus we talk with Jake Abernethy of the University of Michigan about municipal data and his work on the Flint water crisis. 

Perturb-and-MAP and Machine Learning in the Flint Water Crisis

In episode fifteen of season two, we talk about Hamiltonian Monte Carlo, we take a listener question about unbalanced data, plus we talk with Doug Eck of Google’s Magenta project. 

Generative Art and Hamiltonian Monte Carlo

In episode sixteen of season two, we get an introduction to Restricted Boltzmann Machines, we take a listener question about tuning hyperparameters,  plus we talk with Eric Lander of the Broad Institute. 

Eric Lander and Restricted Boltzmann Machines

Talking Machines: Human conversation about machine learning

Talking Machines is your window into the world of machine learning. Your hosts, Katherine Gorman and Ryan Adams, bring you clear conversations with experts in the field, insightful discussions of industry news, and useful answers to your questions.

Machine learning is changing the questions we can ask of the world around us, here we explore how to ask the best questions and what  to do with the answers. 

You can catch new episodes every two weeks on Thursdays through Itunes and SoundCloud. 

Talking Machines

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