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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?

Show Suggested Answer Hide Answer
Suggested Answer: D

Contribute your Thoughts:

Eliseo
4 months 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
4 months ago
D) Regression
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Hershel
4 months ago
C) Knowledge mining
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Thersa
4 months ago
B) Clustering
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Hollis
4 months ago
A) Classification
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Katina
5 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
5 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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Chantell
3 months ago
Definitely, regression is the way to go for this type of prediction task.
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Lettie
3 months ago
I agree, regression is the most suitable for predicting the amount of energy from density.
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Owen
3 months ago
Regression is the best choice for predicting values.
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Junita
3 months ago
Definitely, regression is the way to go for predicting energy values based on density.
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Linn
4 months ago
I agree, regression is the most suitable for this type of prediction task.
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Roosevelt
4 months ago
Regression is the best choice for predicting values.
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Chaya
5 months ago
I'm not sure, but I think Clustering could also be useful to group similar samples together.
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Precious
5 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
5 months ago
I agree with Ronna, Regression makes sense because we need to predict a continuous value.
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Barney
5 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
4 months ago
Regression might be useful to predict the energy output based on density.
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Staci
4 months ago
Knowledge mining could also be beneficial to extract insights from the dataset.
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Dana
4 months ago
I think clustering could help identify patterns in the data.
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Ming
4 months ago
Clustering could group similar samples together for further analysis.
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Jerry
5 months ago
Regression might be useful to predict the energy amount based on density.
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Murray
5 months ago
I think clustering could help identify patterns in the data.
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Ronna
5 months ago
I think we should use Regression for this task.
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Lea
5 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
4 months ago
Yes, regression is the most suitable for this type of prediction task.
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Barbra
4 months ago
I agree, regression would be the best choice for predicting energy based on density.
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