The New DBfication of ML/AI with Arun Kumar
EPISODE 553
|
JANUARY
17,
2022
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About this Episode
Today we’re joined by Arun Kumar, an associate professor at UC San Diego. We had the pleasure of catching up with Arun prior to the Workshop on Databases and AI at NeurIPS 2021, where he delivered the talk “The New DBfication of ML/AI.” In our conversation, we explore this “database-ification” of machine learning, a concept analogous to the transformation of relational SQL computation. We discuss the relationship between the ML and database fields and how the merging of the two could have positive outcomes for the end-to-end ML workflow, and a few tools that his team has developed, Cerebro, a tool for reproducible model selection, and SortingHat, a tool for automating data prep, and how tools like these and others affect Arun’s outlook on the future of machine learning platforms and MLOps.
About the Guest
Arun Kumar
University of California, San Diego
Connect with Arun
Resources
- Video: The New DBfication of ML/AI full talk
- Letter from the Rising Star Award Winner
- Project Cerebro
- Article: CNS and CSE’s Arun Kumar Works Toward Democratizing Deep Learning Systems
- Paper: Cerebro: A Layered Data Platform for Scalable Deep Learning
- Video: Cerebro: A Layered Data Platform for Scalable Deep Learning
- Video: KDD 2021 Deep Learning Day: Talk by Arun Kumar
- Video: I-AIM Seminar 7
- Blog: Cerebro: Efficient and Reproducible Model Selection for Deep Learning
- Talk: Resource-Efficient Deep Learning Model Selection on Apache Spark
- Project SortingHat
- Paper: The ML Data Prep Zoo: Towards Semi-Automatic Data Preparation for ML
- Blog: Using ML to automate data prep for ML
- Video: MLOS Seminar: Arun Kumar
- Video: SortingHat SIGMOD'21
