Deal of The Day! Hurry Up, Grab the Special Discount - Save 25% - Ends In 00:00:00 Coupon code: SAVE25
Welcome to Pass4Success

- Free Preparation Discussions

Amazon Exam MLS-C01 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

Contribute your Thoughts:

Delisa
16 days 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
17 days 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
...
Bok
1 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
Shad
2 days 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
8 days 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 days 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
1 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
Tijuana
3 days ago
Using Model Governance to adjust hyper parameters automatically is a smart move. It can save time and improve accuracy.
upvoted 0 times
...
Sherita
19 days ago
I agree, proactive alerts from CloudWatch alarms would be very useful in detecting performance issues early.
upvoted 0 times
...
Barb
1 months ago
Option B sounds like a good choice. Automatically adjusting hyper parameters could help improve accuracy.
upvoted 0 times
...
...
Glendora
2 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
2 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
2 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
26 days 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
27 days 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
2 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
2 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
2 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
2 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