CertNexus Exam AIP-210 Topic 6 Question 24 Discussion

Actual exam question for CertNexus's AIP-210 exam

Question #: 24
Topic #: 6

[All AIP-210 Questions]

Workflow design patterns for the machine learning pipelines:

AAim to explain how the machine learning model works.

BRepresent a pipeline with directed acyclic graph (DAG).

CSeek to simplify the management of machine learning features.

DSeparate inputs from features.

Show Suggested Answer

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 Nada at Jul 14, 2024, 01:10 AM

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Joye

4 months ago

Ha, imagine if the answer was 'A' - 'Explain how the model works'? That would be like asking a magician to reveal their tricks!

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Kattie

3 months ago

Alpha: Definitely, it's all about efficiency and accuracy in the end.

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My

3 months ago

I agree, it's important for understanding and optimizing the machine learning process.

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Alpha

3 months ago

Yeah, that makes sense. It helps visualize the flow of data in the pipeline.

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Rosalyn

3 months ago

I think the answer is 'B' - Represent a pipeline with directed acyclic graph (DAG).

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Dorinda

4 months ago

Personally, I'd go with B. Visualizing the pipeline as a DAG is just so intuitive for this kind of thing.

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Louis

4 months ago

Hmm, I'm not sure. Separating inputs from features seems like a good idea, but I'm not convinced that's the primary purpose of workflow design patterns.

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