New Year Sale 2026! Hurry Up, Grab the Special Discount - Save 25% - Ends In 00:00:00 Coupon code: SAVE25
Welcome to Pass4Success

- Free Preparation Discussions
Mail Us support@pass4success.com
Location US
Mob_nav_barsMENU

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

Limited Time Offer

25%

Off

Get Premium MLS-C01 Questions as Interactive Web-Based Practice Test or PDF

Contribute your Thoughts:

0/2000 characters
Submit Cancel
Vonda
3 months ago
Totally agree with A, incremental training is key for adapting to new trends!
upvoted 0 times
...
Rasheeda
3 months ago
D makes sense, but why limit to just recent data?
upvoted 0 times
...
Micheline
4 months ago
C sounds interesting, but retraining with only recent data? Not sure that's wise.
upvoted 0 times
...
Deandrea
4 months ago
I disagree, B seems more comprehensive with governance features.
upvoted 0 times
...
Julio
4 months ago
A is the best choice for updating the model and monitoring performance.
upvoted 0 times
...
Mabelle
4 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.
upvoted 0 times
...
Vonda
4 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.
upvoted 0 times
...
Alyce
5 months ago
I think option A sounds familiar because it mentions both updating the model and monitoring, which we practiced in a similar question.
upvoted 0 times
...
Son
5 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.
upvoted 0 times
...
Moira
5 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.
upvoted 0 times
...
Roy
5 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.
upvoted 0 times
...
Eleonore
5 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.
upvoted 0 times
...
Tamie
5 months ago
I don't think XenDesktop supports Runtime Resources, but I should double-check that detail from my notes.
upvoted 0 times
...
Delisa
9 months 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!
upvoted 0 times
...
Aileen
9 months 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.
upvoted 0 times
Mose
8 months ago
Let's go with option D then. It's the most straightforward and effective choice.
upvoted 0 times
...
Shaniqua
8 months ago
Yeah, option D is the most practical and efficient solution for improving accuracy and monitoring the model.
upvoted 0 times
...
Dan
9 months ago
SageMaker Model Monitor will definitely help in keeping track of any performance issues.
upvoted 0 times
...
Dyan
9 months ago
I agree, option D seems like the best choice. Incremental training with recent data is key.
upvoted 0 times
...
...
Bok
10 months 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.
upvoted 0 times
Lennie
8 months 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.
upvoted 0 times
...
Alexis
8 months ago
I agree, but I also have concerns about retraining the model with only recent data. We might lose valuable insights from historical data.
upvoted 0 times
...
Mitzie
9 months ago
I see your point about Option C, but I think sticking with Option A would be more reliable in this situation.
upvoted 0 times
...
Shad
9 months ago
I agree, Option A seems like a solid solution. It's important to stay updated on the model's performance.
upvoted 0 times
...
Melodie
9 months 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.
upvoted 0 times
...
Kallie
9 months ago
Option C with SageMaker Debugger sounds promising. We can set appropriate thresholds and configure it to send alerts through Amazon CloudWatch.
upvoted 0 times
...
...
Brandee
10 months 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.
upvoted 0 times
Nickolas
8 months ago
Let's go with Option B then. It seems like the most comprehensive solution for improving accuracy and receiving notifications.
upvoted 0 times
...
Ernest
8 months ago
It's important to stay on top of model performance issues, and these solutions seem to cover that well.
upvoted 0 times
...
Shanda
8 months ago
I agree, having CloudWatch alarms for proactive alerts is a smart move.
upvoted 0 times
...
Kenneth
8 months ago
Option B sounds like a good choice. Automatically adjusting hyper parameters can be beneficial.
upvoted 0 times
...
Bernardo
9 months ago
Yes, having the system automatically adjust hyper parameters and send notifications for performance issues is a great way to maintain model accuracy.
upvoted 0 times
...
Tijuana
9 months ago
Using Model Governance to adjust hyper parameters automatically is a smart move. It can save time and improve accuracy.
upvoted 0 times
...
Sherita
9 months ago
I agree, proactive alerts from CloudWatch alarms would be very useful in detecting performance issues early.
upvoted 0 times
...
Barb
10 months ago
Option B sounds like a good choice. Automatically adjusting hyper parameters could help improve accuracy.
upvoted 0 times
...
...
Glendora
10 months ago
Hmm, that's a good point. Maybe option C is indeed a more comprehensive solution for improving accuracy and receiving notifications.
upvoted 0 times
...
Jovita
10 months ago
I disagree, I believe option C is better. Debugger with appropriate thresholds can alert the team and retraining the model is crucial.
upvoted 0 times
...
Rozella
10 months 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.
upvoted 0 times
Rolande
10 months ago
I agree, Option A sounds like a solid solution. It's important to stay on top of model performance to ensure accurate predictions.
upvoted 0 times
...
Levi
10 months 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.
upvoted 0 times
...
...
Glendora
10 months ago
I think option A is the best choice. Incremental training can help improve accuracy and Model Monitor can send notifications.
upvoted 0 times
...
Lyla
10 months ago
Hmm, that's a good point. Maybe a combination of both options A and C could be the most effective solution.
upvoted 0 times
...
Corrinne
11 months ago
I disagree, I believe option C is better. Debugger with appropriate thresholds can help detect issues and send alerts for retraining.
upvoted 0 times
...
Lyla
11 months ago
I think option A is the best solution. Incremental training can help improve accuracy and Model Monitor can send notifications.
upvoted 0 times
...

Save Cancel