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

Limited Time Offer

25%

Off

Get Premium AI-900 Questions as Interactive Web-Based Practice Test or PDF

Contribute your Thoughts:

Submit Cancel

Eliseo

3 months ago

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

upvoted 0 times

Chau

3 months ago

D) Regression

upvoted 0 times

...

Hershel

3 months ago

C) Knowledge mining

upvoted 0 times

...

Thersa

3 months ago

B) Clustering

upvoted 0 times

...

Hollis

3 months ago

A) Classification

upvoted 0 times

...

Katina

3 months ago

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

upvoted 0 times

...

Pearly

4 months ago

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

upvoted 0 times

Chantell

2 months ago

Definitely, regression is the way to go for this type of prediction task.

upvoted 0 times

...

Lettie

2 months ago

I agree, regression is the most suitable for predicting the amount of energy from density.

upvoted 0 times

...

Owen

2 months ago

Regression is the best choice for predicting values.

upvoted 0 times

...

Junita

2 months ago

Definitely, regression is the way to go for predicting energy values based on density.

upvoted 0 times

...

Linn

3 months ago

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

upvoted 0 times

...

Roosevelt

3 months ago

Regression is the best choice for predicting values.

upvoted 0 times

...

Chaya

4 months ago

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

upvoted 0 times

...

Precious

4 months ago

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

upvoted 0 times

...

Dorcas

4 months ago

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

upvoted 0 times

...

Barney

4 months ago

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

upvoted 0 times

Shantay

3 months ago

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

upvoted 0 times

...

Staci

3 months ago

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

upvoted 0 times

...

Dana

3 months ago

I think clustering could help identify patterns in the data.

upvoted 0 times

...

Ming

3 months ago

Clustering could group similar samples together for further analysis.

upvoted 0 times

...

Jerry

3 months ago

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

upvoted 0 times

...

Murray

4 months ago

I think clustering could help identify patterns in the data.

upvoted 0 times

...

Ronna

4 months ago

I think we should use Regression for this task.

upvoted 0 times

...

Lea

4 months ago

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

upvoted 0 times

Gwen

3 months ago

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

upvoted 0 times

...

Barbra

3 months ago

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

upvoted 0 times

...