From Remote Graphics Workstation to Machine Learning – GPU for every workload in Azure
Description
Share
Download
Download this episode
- MP3 (18.7 MB)
- Low Quality MP4 (21.6 MB)
- High Quality MP4 (55.8 MB)
- Mid Quality MP4 (40.9 MB)
Download captions
More episodes in this series
What's New in Azure Serverless
Related episodes
Share code and collaborate on your next project using Git and pull requests hosted by VSTS
Building Windows - how the bits flow from check-in to the fast-ring
Using pull requests with Visual Studio Team Services
Git at scale with Git Virtual File System
Moving from Subversion to Git
Get started with Git in Visual Studio Team Services
Git at scale
Git Version Control For Everyone
Git at scale
Using Git with Microsoft Visual Studio Team Foundation Server or Visual Studio Online
The Discussion
-
Nguyenhuyen Very useful to me
-
Abdokader Bonjour,J adore votre coopérative et je souhaite d etre particepant aavec vous MERCI ABDOKADER.
-
CSMR2 Very helpful and much easier to understand than the average git talk!
-
Lee Tickett Interesting watch. We do something similar but it seems a little more intuitive than your solution;
We have a dev branch which everyone feature branches off then raises pull/merge requests once code is ready to merge back into dev.
However, when we are ready to publish/deploy we raise a pull/merge request into master. So master always tracks our production build(s)- no need to spin up MXXX branches and destroy them as you do.
One topic you didn't cover, which I would be interested in; How do you handle your merges? We try to rebase before merging to avoid any conflicts but haven't mastered the rebase process yet. I think we may be over complicating things and should maybe just merge and handle the conflicts. -
Aaron Toth I liked the video and it was nice to see this strategy being advocated again.