DeepQB: Deep Learning to Quantify Quarterback Decision-Making with Brian Burke - TWIML Talk #297

DeepQB: Deep Learning to Quantify Quarterback Decision-Making with Brian Burke - TWIML Talk #297

Today we're joined by Brian Burke, Analytics Specialist with the Stats & Information Group at ESPN. A former Navy pilot and lifelong football fan, Brian saw the correlation between fighter pilots and quarterbacks in the quick decisions both roles make on a regular basis. In this episode, we discuss his paper: “DeepQB: Deep Learning with Player Tracking to Quantify Quarterback Decision-Making & Performance”, what it means for football, and his excitement for machine learning in sports.

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Peering into the Home w/ Aerial.ai's Wifi Motion Analytics - TWiML Talk #107

Peering into the Home w/ Aerial.ai's Wifi Motion Analytics - TWiML Talk #107

In this episode I’m joined by Michel Allegue and Negar Ghourchian of Aerial.ai. Aerial is doing some really interesting things in the home automation space, by using wifi signal statistics to identify...

2 Feb 201840min

Physiology-Based Models for Fitness and Training w/ Firstbeat with Ilkka Korhonen - TWiML Talk #106

Physiology-Based Models for Fitness and Training w/ Firstbeat with Ilkka Korhonen - TWiML Talk #106

In this episode i'm joined by Ilkka Korhonen, Vice President of Technology at Firstbeat, a company whose algorithms are embedded in fitness watches from companies like Garmin and Suunto and which use ...

2 Feb 201835min

Machine Learning for Signal Processing Applications w/ Stuart Feffer & Brady Tsai - TWiML Talk #105

Machine Learning for Signal Processing Applications w/ Stuart Feffer & Brady Tsai - TWiML Talk #105

In this episode, I'm joined by Stuart Feffer, co-founder and CEO of Reality AI, which provides tools and services for engineers working with sensors and signals, and Brady Tsai, Business Development M...

1 Feb 201836min

Personalizing the Ferrari Challenge Experience w/ Intel AI - TWiML Talk #104

Personalizing the Ferrari Challenge Experience w/ Intel AI - TWiML Talk #104

In this episode, I'm joined by Andy Keller and Emile Chin-Dickey to discuss Intel's partnership with the Ferrari Challenge North American Series. Andy is a Deep Learning Data Scientist at Intel and Em...

31 Jan 201837min

Deep Learning for 3D Sensors and Cameras in Lighthouse with Alex Teichman - TWiML Talk #103

Deep Learning for 3D Sensors and Cameras in Lighthouse with Alex Teichman - TWiML Talk #103

In this episode, I sit down with Alex Teichman, CEO and Co-Founder of Lighthouse, a company taking a new approach to the in-home smart camera. Alex and I dig into what exactly the Lighthouse product i...

30 Jan 201842min

Computer Vision for Cozmo, the Cutest Toy Robot Everrrrr! with Andrew Stein - TWiML Talk #102

Computer Vision for Cozmo, the Cutest Toy Robot Everrrrr! with Andrew Stein - TWiML Talk #102

In this episode, I'm joined by Andrew Stein, computer vision engineer at consumer robotics company Anki, and his partner in crime Cozmo, a toy robot with tons of personality. Andrew joined me during t...

30 Jan 201843min

Expectation Maximization, Gaussian Mixtures & Belief Propagation, OH MY! w/ Inmar Givoni - Talk #101

Expectation Maximization, Gaussian Mixtures & Belief Propagation, OH MY! w/ Inmar Givoni - Talk #101

In this episode i'm joined by Inmar Givoni, Autonomy Engineering Manager at Uber ATG, to discuss her work on the paper Min-Max Propagation, which was presented at NIPS last month in Long Beach. Inmar ...

26 Jan 201848min

A Linear-Time Kernel Goodness-of-Fit Test - NIPS Best Paper '17 - TWiML Talk #100

A Linear-Time Kernel Goodness-of-Fit Test - NIPS Best Paper '17 - TWiML Talk #100

In this episode, I speak with Arthur Gretton, Wittawat Jitkrittum, Zoltan Szabo and Kenji Fukumizu, who, alongside Wenkai Xu authored the 2017 NIPS Best Paper Award winner “A Linear-Time Kernel Goodne...

24 Jan 201822min

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