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Amazon MLS-C01 Exam - Topic 5 Question 76 Discussion

A company deployed a machine learning (ML) model on the company website to predict real estate prices. Several months after deployment, an ML engineer notices that the accuracy of the model has gradually decreased.The ML engineer needs to improve the accuracy of the model. The engineer also needs to receive notifications for any future performance issues.Which solution will meet these requirements?
B) Use Amazon SageMaker Model Governance. Configure Model Governance to automatically adjust model hyper para meters. Create a performance threshold alarm in Amazon CloudWatch to send notifications. and D) Use only data from the previous several months to perform incremental training to update the model. Use Amazon SageMaker Model Monitor to detect model performance issues and to send notifications.
A) Perform incremental training to update the model. Activate Amazon SageMaker Model Monitor to detect model performance issues and to send notifications.
C) Use Amazon SageMaker Debugger with appropriate thresholds. Configure Debugger to send Amazon CloudWatch alarms to alert the team Retrain the model by using only data from the previous several months.

Amazon MLS-C01 Exam - Topic 5 Question 76 Discussion

Actual exam question for Amazon's MLS-C01 exam
Question #: 76
Topic #: 5
[All MLS-C01 Questions]

A company deployed a machine learning (ML) model on the company website to predict real estate prices. Several months after deployment, an ML engineer notices that the accuracy of the model has gradually decreased.

The ML engineer needs to improve the accuracy of the model. The engineer also needs to receive notifications for any future performance issues.

Which solution will meet these requirements?

Show Suggested Answer Hide Answer
Suggested Answer: B, D

https://www.redhat.com/en/topics/devops/what-is-blue-green-deployment

by Jutta at Jul 09, 2023, 12:57 PM

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Vonda
8 months ago
Totally agree with A, incremental training is key for adapting to new trends!
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Rasheeda
8 months ago
D makes sense, but why limit to just recent data?
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Micheline
8 months ago
C sounds interesting, but retraining with only recent data? Not sure that's wise.
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Deandrea
9 months ago
I disagree, B seems more comprehensive with governance features.
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Julio
9 months ago
A is the best choice for updating the model and monitoring performance.
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Mabelle
9 months ago
I recall that using recent data for retraining can help, but I’m not certain if just using the last few months is enough for a good model update.
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Vonda
9 months ago
I’m a bit confused about the difference between Model Monitor and Model Governance. I feel like I might have mixed them up in my notes.
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Alyce
9 months ago
I think option A sounds familiar because it mentions both updating the model and monitoring, which we practiced in a similar question.
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Son
10 months ago
I remember we discussed the importance of incremental training in class, but I'm not sure if it's the best approach here.
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Moira
10 months ago
This looks like a straightforward question about business analysis deliverables. I'll carefully review the options and think about which one best captures the agreed-upon information from the BAs and stakeholders.
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Roy
10 months ago
Okay, let me think this through step-by-step. SteelCentral Portal is a monitoring and analytics tool, so it makes sense that it would be available as a software module or virtual appliance. I'm leaning towards option C, the .ova file for ESX, but I'll double-check my notes to be sure.
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Eleonore
10 months ago
Option D seems like the most definitive answer - that XenDesktop is not a supported platform for the Runtime Resource. I'm leaning towards that, but I want to double-check the other options just to be sure.
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Tamie
10 months ago
I don't think XenDesktop supports Runtime Resources, but I should double-check that detail from my notes.
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Delisa
1 year ago
So the model's performance is slipping, huh? I guess you could say it's having a 'housing crisis' of its own. Time to whip it back into shape before it ends up living in a cardboard box!
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Aileen
1 year ago
D is the clear winner for me. Using recent data for incremental training is a no-brainer, and SageMaker Model Monitor will keep an eye on things. Plus, it's the most straightforward option - no need to mess with all that fancy governance or debugging stuff.
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Mose
1 year ago
Let's go with option D then. It's the most straightforward and effective choice.
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Shaniqua
1 year ago
Yeah, option D is the most practical and efficient solution for improving accuracy and monitoring the model.
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Dan
1 year ago
SageMaker Model Monitor will definitely help in keeping track of any performance issues.
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Dyan
1 year ago
I agree, option D seems like the best choice. Incremental training with recent data is key.
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Bok
1 year ago
Option C with SageMaker Debugger looks interesting, but I'm not sure about the whole 'retrain with only the last few months of data' part. Seems like we might be losing valuable historical information.
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Lennie
1 year ago
Maybe we can combine elements from different options to find a solution that works best for us. Incremental training with Model Monitor could be a good approach.
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Alexis
1 year ago
I agree, but I also have concerns about retraining the model with only recent data. We might lose valuable insights from historical data.
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Mitzie
1 year ago
I see your point about Option C, but I think sticking with Option A would be more reliable in this situation.
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Shad
1 year ago
I agree, Option A seems like a solid solution. It's important to stay updated on the model's performance.
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Melodie
1 year ago
I think Option A is the best choice. Incremental training can update the model and SageMaker Model Monitor will send notifications for any performance issues.
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Kallie
1 year ago
Option C with SageMaker Debugger sounds promising. We can set appropriate thresholds and configure it to send alerts through Amazon CloudWatch.
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Brandee
1 year ago
I like the idea of using Model Governance in option B. Automatically adjusting the hyper parameters could be really helpful, and the CloudWatch alarms will give us proactive alerts. That's a clever approach.
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Nickolas
1 year ago
Let's go with Option B then. It seems like the most comprehensive solution for improving accuracy and receiving notifications.
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Ernest
1 year ago
It's important to stay on top of model performance issues, and these solutions seem to cover that well.
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Shanda
1 year ago
I agree, having CloudWatch alarms for proactive alerts is a smart move.
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Kenneth
1 year ago
Option B sounds like a good choice. Automatically adjusting hyper parameters can be beneficial.
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Bernardo
1 year ago
Yes, having the system automatically adjust hyper parameters and send notifications for performance issues is a great way to maintain model accuracy.
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Tijuana
1 year ago
Using Model Governance to adjust hyper parameters automatically is a smart move. It can save time and improve accuracy.
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Sherita
1 year ago
I agree, proactive alerts from CloudWatch alarms would be very useful in detecting performance issues early.
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Barb
1 year ago
Option B sounds like a good choice. Automatically adjusting hyper parameters could help improve accuracy.
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Glendora
1 year ago
Hmm, that's a good point. Maybe option C is indeed a more comprehensive solution for improving accuracy and receiving notifications.
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Jovita
1 year ago
I disagree, I believe option C is better. Debugger with appropriate thresholds can alert the team and retraining the model is crucial.
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Rozella
1 year ago
Option A seems like the way to go. Incremental training is a great way to keep the model up-to-date, and SageMaker Model Monitor will make it easy to catch any performance issues. Sounds like a solid solution.
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Rolande
1 year ago
I agree, Option A sounds like a solid solution. It's important to stay on top of model performance to ensure accurate predictions.
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Levi
1 year ago
Option A seems like the best choice. Incremental training will help keep the model accurate, and Model Monitor will alert us to any issues.
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Glendora
1 year ago
I think option A is the best choice. Incremental training can help improve accuracy and Model Monitor can send notifications.
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Lyla
1 year ago
Hmm, that's a good point. Maybe a combination of both options A and C could be the most effective solution.
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Corrinne
1 year ago
I disagree, I believe option C is better. Debugger with appropriate thresholds can help detect issues and send alerts for retraining.
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Lyla
1 year ago
I think option A is the best solution. Incremental training can help improve accuracy and Model Monitor can send notifications.
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