
Changelog Master Feed
MLOps and tracking experiments with Allegro AI (Practical AI #97)
Jul 20, 2020 · 51 min · 49.2 MB
0:00-51:08
Streams straight from the publisher. podnod never proxies or re-hosts episode audio.
DevOps for deep learning is well… different. You need to track both data and code, and you need to run multiple different versions of your code for long periods of time on accelerated hardware. Allegro AI is helping data scientists manage these workflows with their open source MLOps solution called Trains. Nir Bar-Lev, Allegro’s CEO, joins us to discuss their approach to MLOps and how to make deep learning development more robust.
Changelog++ members save 3 minutes on this episode because they made the ads disappear. Join today!
Sponsors:
- DigitalOcean – DigitalOcean’s developer cloud makes it simple to launch in the cloud and scale up as you grow. They have an intuitive control panel, predictable pricing, team accounts, worldwide availability with a 99.99% uptime SLA, and 24/7/365 world-class support to back that up. Get your $100 credit at do.co/changelog.
- Fastly – Our bandwidth partner. Fastly powers fast, secure, and scalable digital experiences. Move beyond your content delivery network to their powerful edge cloud platform. Learn more at fastly.com.
- Rollbar – We move fast and fix things because of Rollbar. Resolve errors in minutes. Deploy with confidence. Learn more at rollbar.com/changelog.
Featuring:
- Nir Bar-Lev – LinkedIn
- Chris Benson – Website, GitHub, LinkedIn, Bluesky, X
- Daniel Whitenack – Website, GitHub, X
Show Notes:
Something missing or broken? PRs welcome!
Trains
github.comJoin the discussion
changelog.zulipchat.comChangelog++
changelog.comDigitalOcean
do.coFastly
fastly.comRollbar
rollbar.comLinkedIn
linkedin.comWebsite
chrisbenson.comGitHub
github.comLinkedIn
linkedin.comBluesky
bsky.appX
x.comWebsite
datadan.ioGitHub
github.comX
x.comAllegro AI
allegro.aiTrains demo server
demoapp.trains.allegro.aiTrains video tutorials on YouTube
youtube.comPRs welcome!
github.com