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CertNexus Exam AIP-210 Topic 3 Question 17 Discussion

Actual exam question for CertNexus's AIP-210 exam
Question #: 17
Topic #: 3
[All AIP-210 Questions]

Workflow design patterns for the machine learning pipelines:

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Suggested Answer: B

Workflow design patterns for machine learning pipelines are common solutions to recurring problems in building and managing machine learning workflows. One of these patterns is to represent a pipeline with a directed acyclic graph (DAG), which is a graph that consists of nodes and edges, where each node represents a step or task in the pipeline, and each edge represents a dependency or order between the tasks. A DAG has no cycles, meaning there is no way to start at one node and return to it by following the edges. A DAG can help visualize and organize the pipeline, as well as facilitate parallel execution, fault tolerance, and reproducibility.


Contribute your Thoughts:

Rima
6 months ago
True, but directed acyclic graphs better fit the workflow design pattern. I agree with B.
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Brock
6 months ago
Simplifying management is crucial, so option C might be correct.
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Pamella
6 months ago
I'm leaning towards option B. DAGs are common in ML workflows.
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Rima
7 months ago
But option C makes sense too; they need to simplify feature management.
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Casie
7 months ago
I think they represent a pipeline with a directed acyclic graph, choice B.
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Pamella
7 months ago
This question seems tricky. What are workflow design patterns for ML pipelines?
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