Causal Models in Practice at Lyft with Sean Taylor - #486

Causal Models in Practice at Lyft with Sean Taylor - #486

Today we’re joined by Sean Taylor, Staff Data Scientist at Lyft Rideshare Labs. We cover a lot of ground with Sean, starting with his recent decision to step away from his previous role as the lab director to take a more hands-on role, and what inspired that change. We also discuss his research at Rideshare Labs, where they take a more “moonshot” approach to solving the typical problems like forecasting and planning, marketplace experimentation, and decision making, and how his statistical approach manifests itself in his work. Finally, we spend quite a bit of time exploring the role of causality in the work at rideshare labs, including how systems like the aforementioned forecasting system are designed around causal models, if driving model development is more effective using business metrics, challenges associated with hierarchical modeling, and much much more. The complete show notes for this episode can be found at twimlai.com/go/486.

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Building a Recommender System from Scratch at 20th Century Fox with JJ Espinoza - TWiML Talk #220

Building a Recommender System from Scratch at 20th Century Fox with JJ Espinoza - TWiML Talk #220

Today we’re joined by JJ Espinoza, former Director of Data Science at 20th Century Fox. In this talk we dig into JJ and his team’s experience building and deploying a content recommendation system fr...

14 Tammi 201934min

Legal and Policy Implications of Model Interpretability with Solon Barocas - TWiML Talk #219

Legal and Policy Implications of Model Interpretability with Solon Barocas - TWiML Talk #219

Today we’re joined by Solon Barocas, Assistant Professor of Information Science at Cornell University. Solon and I caught up to discuss his work on model interpretability and the legal and policy imp...

10 Tammi 201946min

Trends in Computer Vision with Siddha Ganju - TWiML Talk #218

Trends in Computer Vision with Siddha Ganju - TWiML Talk #218

In the final episode of our AI Rewind series, we’re excited to have Siddha Ganju back on the show. Siddha, who is now an autonomous vehicles solutions architect at Nvidia shares her thoughts on trend...

7 Tammi 201932min

Trends in Reinforcement Learning with Simon Osindero - TWiML Talk #217

Trends in Reinforcement Learning with Simon Osindero - TWiML Talk #217

In this episode of our AI Rewind series, we introduce a new friend of the show, Simon Osindero, Staff Research Scientist at DeepMind. We discuss trends in Deep Reinforcement Learning in 2018 and beyo...

3 Tammi 201952min

Trends in Natural Language Processing with Sebastian Ruder - TWiML Talk #216

Trends in Natural Language Processing with Sebastian Ruder - TWiML Talk #216

In this episode of our AI Rewind series, we’ve brought back recent guest Sebastian Ruder, PhD Student at the National University of Ireland and Research Scientist at Aylien, to discuss trends in Natur...

31 Joulu 201852min

Trends in Machine Learning with Anima Anandkumar - TWiML Talk #215

Trends in Machine Learning with Anima Anandkumar - TWiML Talk #215

In this episode of our AI Rewind series, we’re back with Anima Anandkumar, Bren Professor at Caltech and now Director of Machine Learning Research at NVIDIA. Anima joins us to discuss her take on tr...

27 Joulu 201851min

Trends in Deep Learning with Jeremy Howard - TWiML Talk #214

Trends in Deep Learning with Jeremy Howard - TWiML Talk #214

In this episode of our AI Rewind series, we’re bringing back one of your favorite guests of the year, Jeremy Howard, founder and researcher at Fast.ai. Jeremy joins us to discuss trends in Deep Learn...

24 Joulu 20181h 8min

Training Large-Scale Deep Nets with RL with Nando de Freitas - TWiML Talk #213

Training Large-Scale Deep Nets with RL with Nando de Freitas - TWiML Talk #213

Today we close out both our NeurIPS series joined by Nando de Freitas, Team Lead & Principal Scientist at Deepmind. In our conversation, we explore his interest in understanding the brain and working ...

20 Joulu 201855min

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