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CertNexus Exam AIP-210 Topic 2 Question 41 Discussion

Actual exam question for CertNexus's AIP-210 exam
Question #: 41
Topic #: 2
[All AIP-210 Questions]

Which two of the following criteria are essential for machine learning models to achieve before deployment? (Select two.)

Show Suggested Answer Hide Answer
Suggested Answer: C, E

Scalability and explainability are two criteria that are essential for ML models to achieve before deployment. Scalability is the ability of an ML model to handle increasing amounts of data or requests without compromising its performance or quality. Scalability can help ensure that the model can meet the demand and expectations of users or customers, as well as adapt to changing conditions or environments. Explainability is the ability of an ML model to provide clear and intuitive explanations for its predictions or decisions. Explainability can help increase trust and confidence among users or stakeholders, as well as enable accountability and responsibility for the model's actions and outcomes.


Contribute your Thoughts:

Nohemi
1 months ago
Ha, this is easy! Clearly, the answer is C and E. Explainability and scalability are the yin and yang of machine learning. Anything else is just window dressing.
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Micaela
8 days ago
I agree, those two criteria are definitely essential for machine learning models.
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Jaclyn
18 days ago
I think you're right, explainability and scalability are crucial for deployment.
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Daron
1 months ago
Wow, this is a tough one. I'm going with C and E - explainability and scalability are like the peanut butter and jelly of ML models. Gotta have 'em both!
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Elena
2 months ago
Hold up, I think B and E are the real winners here. Data size and scalability are the foundation for any ML model worth its salt. Explainability? That's for the nerds.
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Starr
9 days ago
Portability could also be important for deploying ML models in different environments.
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Malcom
10 days ago
Explainability might not be as important as the other factors.
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Tamra
18 days ago
Complexity and portability are important too, but B and E are top priorities.
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Stefanie
23 days ago
Explainability might be important for some cases, but B and E are definitely key.
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Deane
24 days ago
I agree, data size and scalability are crucial for deployment.
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Evangelina
1 months ago
I agree, data size and scalability are crucial for ML models to succeed.
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Lizette
2 months ago
I think E) Scalability is crucial too. It's important for the model to handle large amounts of data.
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Avery
2 months ago
Hmm, I'd say C and D are the way to go. Portability is key for real-world deployment, and explainability is a must for regulatory compliance.
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Cherry
1 months ago
Explainability is also important for ensuring transparency and trust in the model's predictions.
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Tamekia
1 months ago
I agree, portability is crucial for deploying models across different environments.
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Trevor
2 months ago
C and E are definitely the most important. Who cares about explainability when you can just throw more data at it, right?
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Jeniffer
2 months ago
I agree with you, Sylvia. I also believe D) Portability is essential for deployment.
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Sylvia
3 months ago
I think C) Explainability is important for machine learning models.
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