Talking Machines

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Talking Machines episodes

September 21, 2017 The Long View and Learning in Person
In episode nine of season three we chat about the difference between models and algorithms, take a listener question about summer schools and learning in person as opposed to learning digitally, and we chat with John Quinn of the United Nations Global Pulse lab in Kampala, Uganda and Makerere University's Artificial Intelligence Research group.
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1 hr 6 min
September 08, 2017 Machine Learning in the Field and Bayesian Baked Goods
In episode eight of season three we return to the epic (or maybe not so epic) clash between frequentists and bayesians, take a listener question about the ethical questions generators of machine learning should be asking of themselves (not just their tools) and we hear a conversation with Ernest Mwebaze of Makerere University.
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1 hr
August 10, 2017 Data Science Africa with Dina Machuve
In episode seven of season three we take a minute to break way from our regular format and feature a conversation with Dina Machuve of the Nelson Mandela African Institute of Science and Technology we cover everything from her work to how cell phone access has changed data patterns. We got to talk with her at the Data Science Africa confrence and workshop.

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49 min
July 28, 2017 The Church of Bayes and Collecting Data
In episode six of season three we chat about the difference between frequentists and Bayesians, take a listener question about techniques for panel data, and have an interview with Katherine Heller of Duke

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50 min
July 13, 2017 Getting a Start in ML and Applied AI at Facebook
In episode five of season three we compare and contrast AI and data science, take a listener question about getting started in machine learning, and listen to an interview with Joaquin Quiñonero Candela.
For a great place to get started with foundational ideas in ML, take a look at Andrew Ng’s course on Coursera. Then check out Daphne Kohler’s course.

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58 min
June 29, 2017 Bias Variance Dilemma for Humans and the Arm Farm
In episode four of season three Neil introduces us to the ideas behind the bias variance dilemma (and how how we can think about it in our daily lives). Plus, we answer a listener question about how to make sure your neural networks don't get fooled. Our guest for this episode is Jeff Dean, Google Senior Fellow in the Research Group, where he leads the Google Brain project. We talk about a closet full of robot arms (the arm farm!), image recognition for diabetic retinopathy, and equality in data and the community.

Fun Fact: Geoff Hinton’s distant relative invented the word tesseract. (How cool is that. Seriously.)
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51 min
June 15, 2017 Overfitting and Asking Ecological Questions with ML
In this episode three of season three of Talking Machines we dive into overfitting, take a listener question about unbalanced data and talk with Professor (Emeritus) Tom Dietterich from Oregon State University.
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42 min
May 25, 2017 Graphons and "Inferencing"
In episode two of season three Neil takes us through the basics on dropout, we chat about the definition of inference (It's more about context than you think!) and hear an interview with Jennifer Chayes of Microsoft.
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42 min
April 27, 2017 Hosts of Talking Machines: Neil Lawrence and Ryan Adams
Talking Machines is entering its third season and going through some changes. Our founding host Ryan is moving on and in his place Neil Lawrence of Amazon is taking over as co host. We say thank you and good bye to Ryan with an interview about his work.
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34 min
September 01, 2016 ANGLICAN and Probabilistic Programming
In episode seventeen of season two we get an introduction to Min Hashing, talk with Frank Wood the creator of ANGLICAN, about probabilistic programming and his new company, INVREA, and take a listener question about how to choose an architecture when using a neural network.
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45 min

About Talking Machines

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Talking Machines is your window into the world of machine learning. Your hosts, Katherine Gorman and Neil Lawrence, bring you clear conversations with experts in the field, insightful discussions of…