Stanford MLSys Seminar
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About
Machine learning is driving exciting changes and progress in computing. What does the ubiquity of machine learning mean for how people build and deploy systems and applications? What challenges does industry face when deploying machine learning systems in the real world, and how can academia rise to meet those challenges? Updates every Monday and Friday - old episodes on Mondays, new episodes on Fridays! Check out our website and your YouTube channel for full videos! https://mlsys.stanford.edu/ https://www.youtube.com/channel/UCzz6ructab1U44QPI3HpZEQ
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Recent episodes
- #62 Dan Fu - Improving Transfer and Robustness of Supervised Contrastive Learning
- #61 Kexin Rong - Big Data Analytics
- #60 Igor Markov - Looper: An End-to-End ML Platform for Product Decisions
- #59 Zhuohan Li - Alpa: Automated Model-Parallel Deep Learning
- 3/10/22 #58 Shruti Bhosale - Multilingual Machine Translation
- 3/3/22 #57 Vijay Janapa Reddi - TinyML, Harvard Style
- 2/24/22 #56 Fait Poms - Interactive Model Development
- 1/28/21 #10 Travis Addair - Deep Learning at Scale with Horovod
- 2/17/22 #55 Doris Lee - Visualization for Data Science
- 1/21/21 #9 Song Han - Reducing AI's Carbon Footprint