In episode two I am joined by Even Oldridge, Senior Manager at NVIDIA, who is leading the Merlin Team. These people are working on an open-source framework for building large-scale deep learning recommender systems and have already won numerous RecSys competitions.

We talk about the relevance and impact of deep learning applied to recommender systems as well as the challenges and pitfalls of deep learning based recommender systems. We briefly touch on Even's early data science contributions at PlentyOfFish, a Canadian online-dating platform. Starting with personalized recommendations of people to people he transitioned to realtor, a real-estate marketplace. From the potentially biggest social decision in life to the probably biggest financial decision in life he has really been involved with recommender systems at the extremes. At NVIDIA - to which he refers as the one company that works with all the other AI companies - he pushes for Merlin as large-scale, accessible and efficient platform for developing and deploying recommender systems on GPUs.
This brought him also closer to the community which he served as industry Co-Chair at RecSys in 2021 as well as to winning multiple RecSys competitions with his team in the recent years.

Enjoy this enriching episode of RECSPERTS - Recommender Systems Experts.

Links from this Episode:

• Even Oldridge on LinkedIn and Twitter
• NVIDIA Merlin
• NVIDIA Merlin at GitHub
• Even's upcoming Talk at GTC 2021: Building and Deploying Recommender Systems Quickly and Easily with NVIDIA Merlin
• PlentyOfFish, realtor
• fast.ai
• Twitter RecSys Challenge 2021
• Recommending music on Spotify with Deep Learning

Papers

• Dacrema et al. (2019): Are We Really Making Much Progress? A Worrying Analysis of Recent Neural Recommendation Approaches (best paper award at RecSys 2019)
• Jannach et al. (2020): Why Are Deep Learning Models Not Consistently Winning Recommender Systems Competitions Yet?: A Position Paper
• Moreira et al. (2021): Transformers4Rec: Bridging the Gap between NLP and Sequential / Session-Based Recommendation
• Deotte et al. (2021): GPU Accelerated Boosted Trees and Deep Neural Networks for Better Recommender Systems 

General Links:

• Follow me on Twitter: https://twitter.com/LivesInAnalogia
• Send me your comments, questions and suggestions to marcel@recsperts.com
• Podcast Website: https://www.recsperts.com/