Microsoft Exam AI-900 Topic 1 Question 68 Discussion

Actual exam question for Microsoft's AI-900 exam

Question #: 68
Topic #: 1

[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?

AClassification

BClustering

CKnowledge mining

DRegression

Show Suggested Answer

Suggested Answer: D

by Reed at Jul 01, 2024, 11:13 AM

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Eliseo

26 days ago

Wow, this exam question is as dense as the fuel samples! I'm going with D - Regression, just like my love life.

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Chau

12 days ago

D) Regression

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Hershel

13 days ago

C) Knowledge mining

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Thersa

18 days ago

B) Clustering

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Hollis

19 days ago

A) Classification

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Katina

1 months ago

I believe Classification is the right choice, as we need to categorize the samples based on their energy potential.

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Pearly

1 months ago

Classification? Nah, that's for when you're trying to categorize things, not predict values. Regression is definitely the way to go.

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Linn

10 days ago

I agree, regression is the most suitable for this type of prediction task.

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Roosevelt

25 days ago

Regression is the best choice for predicting values.

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Chaya

1 months ago

I'm not sure, but I think Clustering could also be useful to group similar samples together.

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Precious

1 months ago

Knowledge mining? What is this, a treasure hunt? I'd say regression is the way to solve this problem.

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Dorcas

1 months ago

I agree with Ronna, Regression makes sense because we need to predict a continuous value.

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Barney

1 months ago

Regression? Really? I'm thinking clustering might be a better approach to understand the relationships in the data.

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Shantay

16 days ago

Regression might be useful to predict the energy output based on density.

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Staci

19 days ago

Knowledge mining could also be beneficial to extract insights from the dataset.

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Dana

20 days ago

I think clustering could help identify patterns in the data.

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Ming

27 days ago

Clustering could group similar samples together for further analysis.

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Jerry

1 months ago

Regression might be useful to predict the energy amount based on density.

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Murray

1 months ago

I think clustering could help identify patterns in the data.

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Ronna

2 months ago

I think we should use Regression for this task.

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Lea

2 months ago

Hmm, this looks like a regression problem to me. I bet option D is the way to go here.

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Gwen

27 days ago

Yes, regression is the most suitable for this type of prediction task.

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Barbra

29 days ago

I agree, regression would be the best choice for predicting energy based on density.

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