ML skills can be created, stopped, redeployed, updated to a new package version, rolled back to a previous package version, modified to use or not use GPU. modified to use or not use Al units, made public or private, or deleted.
B.
ML skills can be created, stopped, redeployed, updated to a new package version, rolled back to a previous package version, made public or private, or deleted.
C.
ML skills can be created, stopped, redeployed, updated to a new package version, rolled back to a previous package version, modified to use or not use GPU. made public or private, or deleted.
D.
ML skills can be created, updated to a new package version, rolled back to a previous package version, modified to use or not use GPU. made public or private, or deleted.
In UiPath AI Center, ML Skills can be managed in various ways, allowing users to customize and control how these skills are deployed and used. The management options include:
Creating a new ML skill.
Stopping a deployed skill.
Redeploying an ML skill.
Updating to a new package version.
Rolling back to a previous version if needed.
Modifying GPU usage.
Modifying the use of AI units.
Making the skill public or private.
Deleting an ML skill when no longer needed.
This provides flexibility for both managing the ML infrastructure and optimizing resources in real-time.
For more details, refer to:
UiPath AI Center Documentation: Managing ML Skills
ML Skill Management Options: Managing Machine Learning Skills in AI Center
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