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

Chai Time Data Science

Video Version: https://youtu.be/W3aWEXqIkWk

Blog Overview: http://sanyambhutani.com/interview-with-the-nvidia-acm-recsys-2021-winning-team

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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 & Researchers, and all things Data Science hosted by Sanyam Bhutani.