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A team is experimenting with traditional models for a classification workflow in Azure Machine Learning.
The team requires a consistent way to manage assets that are created during experimentation.
You need to ensure that artifacts can be reused and governed across projects.
Which asset should you register?
Suggested Answer: A
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19 comments · newest first
RI
Rima
24 days ago
Each asset has its role, but we need to prioritize.
FL
Flo
29 days ago
I just feel Models are the key focus here.
RE
Rex
1 month ago
Components can be shared easily across teams. That's a plus.
GA
Gail
1 month ago
Environment can help in different projects. Very important!
RI
Rima
1 month ago
Still, without a solid Pipeline, the Model is useless.
FL
Flo
2 months ago
True, but Models are what we ultimately deploy.
RE
Rex
2 months ago
I lean towards Component. It allows for modular reuse.
GA
Gail
2 months ago
Environment is crucial too. It ensures consistency.
RI
Rima
2 months ago
But what about the Pipeline? It manages the workflow.
FL
Flo
2 months ago
I think we should register the Model. It's the main output.
CH
Chu
3 months ago
I’m leaning towards D) Pipeline, but not sure if it’s the best choice.
JO
Joesph
3 months ago
C) Environment is key for consistency across projects!
JE
Jenise
3 months ago
Wait, can we really reuse environments like that?
XO
Xochitl
3 months ago
I think B) Component makes more sense for managing assets.
WI
Wilbert
3 months ago
Definitely go with A) Model for reusability.
SH
Shay
3 months ago
I thought Components were important for reusability, but I’m not clear if they fit the governance aspect the question is asking about.
AD
Adolph
4 months ago
I have a hunch that the Pipeline might be the right answer because it orchestrates everything, but I can't recall if it’s the best for managing assets specifically.
JU
Judy
4 months ago
I remember practicing with a similar question, and I think registering the Environment could help with consistency across projects, but it feels a bit off for this scenario.
AR
Arminda
4 months ago
I think we might need to register the Model since it's the final output of our experiments, but I'm not entirely sure if that's the best choice for governance.