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CertNexus Exam AIP-210 Topic 5 Question 13 Discussion

Actual exam question for CertNexus's AIP-210 exam
Question #: 13
Topic #: 5
[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.


by Roxane at Mar 09, 2024, 04:33 PM

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Yasuko
6 months ago
I think option C) is valuable as it can streamline the management of features in machine learning.
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Jenelle
6 months ago
I prefer option B) because representing the pipeline as a DAG can make it easier to visualize.
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Kayleigh
6 months ago
I believe option A) is crucial as it helps in understanding the inner workings of the model.
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Lyda
6 months ago
I agree, they help in structuring the process effectively.
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Tawny
6 months ago
I think workflow design patterns are important for organizing machine learning pipelines.
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Eleonora
6 months ago
Candidate 6: I think they seek to simplify the management of ML features too.
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Stacey
6 months ago
Candidate 5: Separate inputs from features is also a key aspect of workflow design patterns.
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Lou
7 months ago
Candidate 4: I agree, and they also represent a pipeline with a DAG.
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Herminia
7 months ago
Candidate 3: I believe they aim to explain how the model works.
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Annabelle
7 months ago
Candidate 2: Yeah, they help in organizing the steps in the ML process.
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Darrin
7 months ago
Candidate 1: I think workflow design patterns for machine learning pipelines are important.
upvoted 0 times
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