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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]

When should you use semi-supervised learning? (Select two.)

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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.


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Pura
17 hours ago
Hmm, I'm not sure about D. Isn't that more for supervised learning? I'm going with B and C - gotta love those biased datasets!
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Fernanda
7 days ago
I think the correct answers are C and E. Labeling data can be a pain, and using unlabeled data is a great way to leverage semi-supervised learning. High-five to the person who wrote this question!
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Graham
10 days ago
But what about when there is a large amount of unlabeled data available? Shouldn't we use semi-supervised learning then?
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Tatum
14 days ago
I agree with Marvel. It can help us make the most out of the limited labeled data we have.
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Marvel
17 days ago
I think we should use semi-supervised learning when labeling data is challenging and expensive.
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