Carlos Guestrin - Explaining the Predictions of Machine Learning Models - TWiML Talk #7

Carlos Guestrin - Explaining the Predictions of Machine Learning Models - TWiML Talk #7

My guest this time is Carlos Guestrin, the Amazon professor of Machine Learning at the University of Washington. Carlos and I recorded this podcast at a conference, shortly after Apple's acquisition of his company Turi. Our focus for this podcast is the explainability of machine learning algorithms. In particular, we discuss some interesting new research published by his team at U of W. The notes for this show can be found at twimlai.com/talk/7.

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How a Global Energy Company Adopts ML & AI with Nicholas Osborn - TWiML Talk #150

How a Global Energy Company Adopts ML & AI with Nicholas Osborn - TWiML Talk #150

On today’s show I’m excited to share this interview with Nick Osborn, a longtime listener of the show and Leader of the Global Machine Learning Project Management Office at AES Corporation, a Fortune ...

14 Juni 201846min

Problem Formulation for Machine Learning with Romer Rosales - TWiML Talk #149

Problem Formulation for Machine Learning with Romer Rosales - TWiML Talk #149

In this episode, i'm joined by Romer Rosales, Director of AI at LinkedIn. We begin with a discussion of graphical models and approximate probability inference, and he helps me make an important connec...

11 Juni 201850min

AI for Materials Discovery with Greg Mulholland - TWiML Talk #148

AI for Materials Discovery with Greg Mulholland - TWiML Talk #148

In this episode I’m joined by Greg Mulholland, Founder and CEO of Citrine Informatics, which is applying AI to the discovery and development of new materials. Greg and I start out with an exploration ...

7 Juni 201842min

Data Innovation & AI at Capital One with Adam Wenchel - TWiML Talk #147

Data Innovation & AI at Capital One with Adam Wenchel - TWiML Talk #147

In this episode I’m joined by Adam Wenchel, vice president of AI and Data Innovation at Capital One, to discuss how Machine Learning & AI are being integrated into their day-to-day practices, and how ...

4 Juni 201845min

Deep Gradient Compression for Distributed Training with Song Han - TWiML Talk #146

Deep Gradient Compression for Distributed Training with Song Han - TWiML Talk #146

On today’s show I chat with Song Han, assistant professor in MIT’s EECS department, about his research on Deep Gradient Compression. In our conversation, we explore the challenge of distributed traini...

31 Maj 201846min

Masked Autoregressive Flow for Density Estimation with George Papamakarios - TWiML Talk #145

Masked Autoregressive Flow for Density Estimation with George Papamakarios - TWiML Talk #145

In this episode, University of Edinburgh Phd student George Papamakarios and I discuss his paper “Masked Autoregressive Flow for Density Estimation.” George walks us through the idea of Masked Autoreg...

28 Maj 201834min

Training Data for Computer Vision at Figure Eight with Qazaleh Mirsharif - TWiML Talk #144

Training Data for Computer Vision at Figure Eight with Qazaleh Mirsharif - TWiML Talk #144

For today’s show, the last in our TrainAI series, I'm joined by Qazaleh Mirsharif, a machine learning scientist working on computer vision at Figure Eight. Qazaleh and I caught up at the TrainAI confe...

25 Maj 201821min

Agile Data Science with Sarah Aerni - TWiML Talk #143

Agile Data Science with Sarah Aerni - TWiML Talk #143

Today we continue our TrainAI series with Sarah Aerni, Director of Data Science at Salesforce Einstein. Sarah and I sat down at the TrainAI conference to discuss her talk “Notes from the Field: The Pl...

24 Maj 201838min

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