Benedikt Schifferer's guest appearances

Benedikt Schifferer

Chai Time Data Science 

Jeremy Howard

Sara Hooker

Ines Montani

Judy Gichoya

Rachel Thomas

Anthony Goldbloom

Andrew Shaw

Richard Craib

John Miller

Ian Ozsvald

Michael Kennedy

Bryan Catanzaro

Jose Fernandez

Marios Michailidis

Samuel Castro

OwlTail

Even Oldridge

Chris Deotte

Bo Liu

Video Version: https://youtu.be/W3aWEXqIkWk  Blog Overview: http://sanyambhutani.com/interview-with-the-nvidia-acm-recsys-2021-winning-team  Subscribe here to the newsletter: https://tinyletter.com/sanyambhutani  In this Episode, Sanyam Bhutani interviews a panel from the ACM RecSys Winning competition team at NVIDIA. They explain why are RecSys systems such a hard problem, how can GPUs accelerate these, how do we productize such solutions. The team also does a ground basic to a complete overview of their solution. They understand the team's approaches to the problem, how did they arrive at the solution, and the tricks that they discovered and very generously shared in this interview  Links:  Interview with Even Oldridge: https://youtu.be/-WzXIV8P_Jk  Interview with Chris Deotte: https://youtu.be/QGCvycOXs2M  Open Source Solution: https://github.com/NVIDIA-Merlin/competitions/tree/main/RecSys2021_Challenge  Paper Link: https://github.com/NVIDIA-Merlin/competitions/blob/main/RecSys2021_Challenge/GPU-Accelerated-Boosted-Trees-and-Deep-Neural-Networks-for-Better-Recommender-Systems.pdf  Follow:  Benedikt Schifferer: Linkedin: https://www.linkedin.com/in/benedikt-schifferer/  Bo Liu: Twitter: https://twitter.com/boliu0 Kaggle: https://www.kaggle.com/boliu0  Chris Deotte: Twitter: https://twitter.com/ChrisDeotte Kaggle: https://www.kaggle.com/cdeotte  Even Oldridge Twitter: https://twitter.com/even_oldridge Linkedin: https://www.linkedin.com/in/even-oldridge/  Sanyam Bhutani: https://twitter.com/bhutanisanyam1 Blog: sanyambhutani.com  About: https://sanyambhutani.com/tag/chaitimedatascience/ A show for Interviews with Practitioners, Kagglers &amp; Researchers, and all things Data Science hosted by Sanyam Bhutani. 

Video Version: <a href="https://youtu.be/W3aWEXqIkWk" rel="nofollow" target="_blank">https://youtu.be/W3aWEXqIkWk</a> Blog Overview: <a href="http://sanyambhutani.com/interview-with-the-nvidia-acm-recsys-2021-winning-team" rel="nofollow" target="_blank">http://sanyambhutani.com/interview-with-the-nvidia-acm-recsys-2021-winning-team</a> Subscribe here to the newsletter: <a href="https://tinyletter.com/sanyambhutani" rel="nofollow" target="_blank">https://tinyletter.com/sanyambhutani</a> In this Episode, Sanyam Bhutani interviews a panel from the ACM RecSys Winning competition team at NVIDIA. They explain why are RecSys systems such a hard problem, how can GPUs accelerate these, how do we productize such solutions. The team also does a ground basic to a complete overview of their solution. They understand the team's approaches to the problem, how did they arrive at the solution, and the tricks that they discovered and very generously shared in this interview Links: Interview with Even Oldridge: <a href="https://youtu.be/-WzXIV8P_Jk" rel="nofollow" target="_blank">https://youtu.be/-WzXIV8P_Jk</a> Interview with Chris Deotte: <a href="https://youtu.be/QGCvycOXs2M" rel="nofollow" target="_blank">https://youtu.be/QGCvycOXs2M</a> Open Source Solution: <a href="https://github.com/NVIDIA-Merlin/competitions/tree/main/RecSys2021_Challenge" rel="nofollow" target="_blank">https://github.com/NVIDIA-Merlin/competitions/tree/main/RecSys2021_Challenge</a> Paper Link: <a href="https://github.com/NVIDIA-Merlin/competitions/blob/main/RecSys2021_Challenge/GPU-Accelerated-Boosted-Trees-and-Deep-Neural-Networks-for-Better-Recommender-Systems.pdf" rel="nofollow" target="_blank">https://github.com/NVIDIA-Merlin/competitions/blob/main/RecSys2021_Challenge/GPU-Accelerated-Boosted-Trees-and-Deep-Neural-Networks-for-Better-Recommender-Systems.pdf</a> Follow: Benedikt Schifferer: Linkedin: <a href="https://www.linkedin.com/in/benedikt-schifferer/" rel="nofollow" target="_blank">https://www.linkedin.com/in/benedikt-schifferer/</a> Bo Liu: Twitter: <a href="https://twitter.com/boliu0" rel="nofollow" target="_blank">https://twitter.com/boliu0</a> Kaggle: <a href="https://www.kaggle.com/boliu0" rel="nofollow" target="_blank">https://www.kaggle.com/boliu0</a> Chris Deotte: Twitter: <a href="https://twitter.com/ChrisDeotte" rel="nofollow" target="_blank">https://twitter.com/ChrisDeotte</a> Kaggle: <a href="https://www.kaggle.com/cdeotte" rel="nofollow" target="_blank">https://www.kaggle.com/cdeotte</a> Even Oldridge Twitter: <a href="https://twitter.com/even_oldridge" rel="nofollow" target="_blank">https://twitter.com/even_oldridge</a> Linkedin: <a href="https://www.linkedin.com/in/even-oldridge/" rel="nofollow" target="_blank">https://www.linkedin.com/in/even-oldridge/</a> Sanyam Bhutani: <a href="https://twitter.com/bhutanisanyam1" rel="nofollow" target="_blank">https://twitter.com/bhutanisanyam1</a> Blog: <a href="http://sanyambhutani.com" rel="nofollow" target="_blank">sanyambhutani.com</a> About: <a href="https://sanyambhutani.com/tag/chaitimedatascience/" rel="nofollow" target="_blank">https://sanyambhutani.com/tag/chaitimedatascience/</a> A show for Interviews with Practitioners, Kagglers &amp; Researchers, and all things Data Science hosted by Sanyam Bhutani.

ACM RecSys Winning Solution: Benedikt Schifferer, Bo Liu, Chris Deotte, Even Oldridge #136