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Amazon Exam CLF-C02 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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Annita
7 months ago
Haha, Stefania's got a point. SageMaker is the duct tape of ML services - it just solves everything!
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Lilli
6 months 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
6 months ago
I think Amazon Personalize could also be a good option for creating personalized recommendations.
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Joseph
6 months ago
I agree, SageMaker is definitely a versatile tool for building and deploying ML models.
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Stefania
7 months ago
SageMaker all the way! Anything else would be like trying to build a house with a screwdriver.
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Brandon
7 months 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
6 months ago
SageMaker is like the 'Swiss Army Knife' of ML services.
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Felice
6 months ago
Personalize is good, but SageMaker offers more flexibility.
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Pamella
7 months ago
Yeah, SageMaker is a versatile tool for building and deploying ML models.
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William
7 months ago
I think SageMaker is the way to go.
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Alva
7 months 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
7 months ago
Yes, SageMaker has all the tools necessary for the company's requirements.
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Cristen
7 months ago
I think Amazon SageMaker is the best choice for building and deploying ML models.
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Eva
8 months 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
7 months ago
Yes, Amazon SageMaker provides a complete solution for the ML lifecycle.
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Van
7 months ago
I agree, Amazon SageMaker is a great choice for building and deploying ML models.
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Elouise
8 months ago
I think Amazon Comprehend is more suitable for natural language processing tasks, not for building ML models.
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Erasmo
8 months ago
I believe Amazon Personalize could also be a good option for building ML models.
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Glenna
8 months ago
I agree with Margurite, Amazon SageMaker is a great choice for deploying ML models.
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Margurite
8 months ago
I think the company can use Amazon SageMaker for building ML models.
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