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