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Amazon CLF-C02 Exam - Topic 2 Question 26 Discussion

Actual exam question for Amazon's CLF-C02 exam
Question #: 26
Topic #: 2
[All CLF-C02 Questions]

A company wants to build, tram, and deploy machine learning (ML) models.

Which AWS service can the company use to meet this requirement?

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Suggested Answer: D

by Benedict at Aug 27, 2024, 02:19 AM

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Johnson
3 months ago
I thought Amazon Personalize was the best choice for ML too.
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Karan
3 months ago
Amazon Comprehend is more for NLP, not ML model deployment.
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Eve
3 months ago
Wait, can you really use SageMaker for all those tasks? Sounds too good!
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Kirk
4 months ago
I agree, SageMaker is the go-to for that.
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Susana
4 months ago
Definitely Amazon SageMaker for building and deploying ML models!
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Eleni
4 months ago
I feel like Amazon Comprehend is more about natural language processing, so it probably isn't the right choice here.
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Shawnda
4 months ago
I’m a bit confused; I thought Amazon Personalize was for recommendations, not general ML model deployment.
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Mickie
4 months ago
I remember practicing a question about AWS services for ML, and SageMaker was definitely mentioned as a key service.
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Cordie
5 months ago
I think the answer might be Amazon SageMaker since it’s specifically designed for building and deploying ML models, but I'm not entirely sure.
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Erin
5 months ago
I feel pretty confident about this one. Amazon SageMaker is the go-to service for end-to-end ML model development and deployment, so that's the answer I'm going with.
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Victor
5 months ago
I'm a bit confused on this one. There are a few different AWS ML services that could potentially fit the bill. I'll need to review the key features of each one to determine the best fit for this use case.
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Tamra
5 months ago
Okay, let me see. The question is asking about a service that can build, train, and deploy ML models, so that rules out some of the more specialized services like Comprehend and Forecast. I'm leaning towards SageMaker, but I'll double-check the other options just to be sure.
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Malika
5 months ago
Hmm, I'm not entirely sure about this one. I know Amazon has a bunch of different ML services, but I'm not super familiar with the details of each one. I'll have to think this through carefully.
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Hyun
5 months ago
I think this is a pretty straightforward question. Amazon SageMaker seems like the obvious choice here since it's a fully managed service for building, training, and deploying ML models.
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Linsey
5 months ago
Hmm, I'm a bit confused. Do we need to associate a specific work type or skill to the maintenance plan as well? I'm not sure if just the auto-generation is enough.
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Annita
1 year ago
Haha, Stefania's got a point. SageMaker is the duct tape of ML services - it just solves everything!
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Lilli
1 year ago
True, SageMaker is like the Swiss Army knife of ML services, it can handle a lot of different tasks.
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Kayleigh
1 year ago
I think Amazon Personalize could also be a good option for creating personalized recommendations.
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Joseph
1 year ago
I agree, SageMaker is definitely a versatile tool for building and deploying ML models.
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Stefania
1 year ago
SageMaker all the way! Anything else would be like trying to build a house with a screwdriver.
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Brandon
1 year ago
Hmm, I was thinking Personalize, but SageMaker does sound like the better fit. Can't go wrong with the 'Swiss Army Knife' of ML services.
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Kimbery
1 year ago
SageMaker is like the 'Swiss Army Knife' of ML services.
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Felice
1 year ago
Personalize is good, but SageMaker offers more flexibility.
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Pamella
1 year ago
Yeah, SageMaker is a versatile tool for building and deploying ML models.
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William
1 year ago
I think SageMaker is the way to go.
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Alva
1 year ago
I agree, SageMaker is the way to go. It's got everything the company needs, and it's a well-established AWS service.
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Adela
1 year ago
Yes, SageMaker has all the tools necessary for the company's requirements.
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Cristen
1 year ago
I think Amazon SageMaker is the best choice for building and deploying ML models.
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Eva
1 year ago
Amazon SageMaker seems like the most comprehensive option here. It covers the entire ML lifecycle, from building to deploying models.
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Quentin
1 year ago
Yes, Amazon SageMaker provides a complete solution for the ML lifecycle.
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Van
1 year ago
I agree, Amazon SageMaker is a great choice for building and deploying ML models.
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Elouise
1 year ago
I think Amazon Comprehend is more suitable for natural language processing tasks, not for building ML models.
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Erasmo
1 year ago
I believe Amazon Personalize could also be a good option for building ML models.
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Glenna
2 years ago
I agree with Margurite, Amazon SageMaker is a great choice for deploying ML models.
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Margurite
2 years ago
I think the company can use Amazon SageMaker for building ML models.
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