Microsoft Exam DP-100 Topic 9 Question 44 Discussion

Actual exam question for Microsoft's DP-100 exam

Question #: 44
Topic #: 9

[All DP-100 Questions]

You have a dataset that includes confidential dat

a. You use the dataset to train a model.

You must use a differential privacy parameter to keep the data of individuals safe and private.

You need to reduce the effect of user data on aggregated results.

What should you do?

ADecrease the value of the epsilon parameter to reduce the amount of noise added to the data

BIncrease the value of the epsilon parameter to decrease privacy and increase accuracy

CDecrease the value of the epsilon parameter to increase privacy and reduce accuracy

DSet the value of the epsilon parameter to 1 to ensure maximum privacy

Show Suggested Answer

Suggested Answer: C

Differential privacy tries to protect against the possibility that a user can produce an indefinite number of reports to eventually reveal sensitive data. A value known as epsilon measures how noisy, or private, a report is. Epsilon has an inverse relationship to noise or privacy. The lower the epsilon, the more noisy (and private) the data is.

https://docs.microsoft.com/en-us/azure/machine-learning/concept-differential-privacy

by Melodie at May 09, 2022, 07:11 PM

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Franchesca

5 days ago

Hmm, this looks like a tricky networking question. I'll need to carefully read through the options and think about the implications of each choice.

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Skye

15 days ago

Application Insights Profiler is great for in-depth performance analysis, but it doesn't sound like the right fit for this question. I'm leaning towards Smart Detection or Continuous export.

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Staci

18 days ago

Okay, let's see. Since the instances are configured to block project-wide SSH keys, that rules out option D. I'm leaning towards option C, but I'll double-check the details.

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Dalene

19 days ago

I think I've got this one figured out. The key is to use a load balancer that can handle path-based routing, which would be the most efficient way to route traffic to the different microservices. Option C, the Application Load Balancer, seems like the best choice here.

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