Stanford MLSys Seminar
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
Also Available on
Share & Embed
Available episodes
24
Typical release rate
Weekly
Latest episode
4 years ago
April 27, 2022
Podcast Privacy Information
Anchor (from Spotify)
Stats, Tracking, Dynamic Audio
Stats: This service collects and aggregates basic information about its listenership, like total download numbers and downloads by date or region.
Tracking: This service may track an individual listener's browsing habits across podcasts and websites. This is typically used to measure advertising conversions. Podbay does not collect any Tracking data.
Dynamic Audio: This service may insert dynamic audio (usually for targeted advertising) into episodes on a per-download or per-stream basis. This could be as basic as factoring in the date or the user's overall region, or when used with Tracking, could be based on more personal user data.
All content for Stanford MLSys Seminar is the property of Dan Fu, Karan Goel, Fiodar Kazhamakia, Piero Molino, Matei Zaharia, Chris Ré and is served directly from their servers with no modification, redirects, or rehosting. The podcast is not affiliated with or endorsed by Podbay in any way.