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Microsoft AI-900 Exam - Topic 4 Question 65 Discussion

Actual exam question for Microsoft's AI-900 exam
Question #: 65
Topic #: 4
[All AI-900 Questions]

You have a dataset that contains experimental data for fuel samples.

You need to predict the amount of energy that can be obtained from a sample based on its density.

Which type of Al workload should you use?

Show Suggested Answer Hide Answer
Suggested Answer: D

by Maybelle at May 23, 2024, 10:12 AM

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Refugia
3 months ago
Knowledge mining? Not sure that’s relevant here.
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Percy
3 months ago
Clustering seems off for this. We need a specific prediction, not groups.
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Lanie
3 months ago
Wait, can you really predict energy just from density? Sounds too simple.
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Jovita
4 months ago
Definitely regression! It fits the scenario perfectly.
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Dean
4 months ago
I think regression is the way to go for predicting energy from density.
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Roxane
4 months ago
I’m leaning towards classification, but now that I think about it, we’re not categorizing here, so maybe regression is the better choice.
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Desmond
4 months ago
Clustering seems like it could be relevant, but I feel like that's more for grouping data rather than predicting a specific value.
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Pamella
4 months ago
I remember practicing a similar question where we had to predict outcomes based on numerical inputs. I think regression was the answer there too.
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Mila
5 months ago
I think we might need to use regression since we're predicting a continuous value, right? But I'm not entirely sure.
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Lilli
5 months ago
I'm a bit confused by the wording of the question. Is it asking about the type of AI workload, or the specific machine learning algorithm? I'll need to clarify that before I can confidently select an answer.
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Bernardo
5 months ago
Regression is definitely the way to go here. We need to predict a continuous value (energy) based on a feature (density), so a regression model is the obvious choice.
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Leigha
5 months ago
This seems like a straightforward regression problem to me. I'll focus on selecting the right regression model and tuning the hyperparameters to get the best performance.
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Twila
5 months ago
Hmm, I'm not sure if this is a regression problem or a classification problem. The question is a bit ambiguous. I'll need to think it through carefully before deciding on the right approach.
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Huey
5 months ago
I'm a bit confused by this question. Does Vault have some special DNS requirements that I'm not aware of? I'll have to review the Vault documentation again before answering.
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France
5 months ago
I'm a bit confused here. Is the Coherence Server involved in this deployment? If so, option A might be the correct answer, but I'll need to double-check the details.
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Rory
5 months ago
This is a good opportunity to demonstrate my understanding of Cisco IKE configuration. I've got this one!
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Lawana
5 months ago
I feel pretty confident about this one. The options seem straightforward, and I know the characteristics of business process steps that are not suitable for service encapsulation.
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Justine
5 months ago
Okay, let me think this through. The key is understanding the tradeoffs between the consensus mechanisms.
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Becky
2 years ago
Regression? That's a no-brainer. Unless, of course, the dataset contains sentient fuel samples that can make their own decisions. In that case, we might need classification. But I doubt it.
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Carin
2 years ago
I agree, regression is the way to go for predicting energy from density.
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Reita
2 years ago
Yeah, unless those fuel samples are making their own decisions, then we might need classification.
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Long
2 years ago
I agree, regression is the way to go for predicting energy based on density.
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Dorinda
2 years ago
Regression? That's a no-brainer.
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Terry
2 years ago
Regression? That's a no-brainer.
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Zana
2 years ago
I agree, regression is the way to go for predicting energy based on density.
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Alva
2 years ago
Regression? That's a no-brainer.
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Rocco
2 years ago
You know, I was thinking about this question while I was fueling up my car. Clearly, it's a regression problem. D all the way!
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Delila
2 years ago
Yes, regression is the way to go for predicting energy based on density. D is the answer.
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Lashon
2 years ago
I agree, it's definitely a regression problem. D is the correct choice.
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Chauncey
2 years ago
Hmm, I don't think we need to get too fancy with clustering or knowledge mining here. Gotta be good old regression, right?
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Cheryll
2 years ago
Density and energy output? Sounds like a job for regression analysis to me. I'm going with D on this one.
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Jolene
2 years ago
I think regression is the best choice for predicting energy output based on density.
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Adell
2 years ago
I'm going with D on this one.
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Leigha
2 years ago
I agree, regression is the way to go for this type of prediction.
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Carry
2 years ago
Density and energy output? Sounds like a job for regression analysis to me.
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