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Amazon MLS-C01 Exam - Topic 3 Question 69 Discussion

Actual exam question for Amazon's MLS-C01 exam
Question #: 69
Topic #: 3
[All MLS-C01 Questions]

A Machine Learning Specialist is using Apache Spark for pre-processing training data As part of the Spark pipeline, the Specialist wants to use Amazon SageMaker for training a model and hosting it Which of the following would the Specialist do to integrate the Spark application with SageMaker? (Select THREE)

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Suggested Answer: A

by Rebecka at Jan 06, 2023, 03:27 AM

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Santos
5 months ago
Not sure about using CSV for inferences, seems outdated.
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Noble
6 months ago
I think downloading the AWS SDK is a must too!
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Yolande
6 months ago
Wait, do we really need to compress data into a ZIP file?
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Rosina
6 months ago
Agree, using the appropriate estimator is key for training.
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Edmond
6 months ago
Definitely need to install the SageMaker Spark library!
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Xochitl
6 months ago
I’m a bit confused about the inference part; I think using the sageMakerModel.transform method sounds right, but I’m not entirely sure if it’s necessary for this question.
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Juliann
6 months ago
I practiced a similar question where we had to upload data to S3, so I feel like compressing the training data into a ZIP file is probably one of the steps.
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Dion
6 months ago
I remember something about using an estimator from the SageMaker Spark Library, but I can't recall if we need to download the AWS SDK too.
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Dorthy
6 months ago
I think we definitely need to install the SageMaker Spark library in the Spark environment, but I'm not sure about the others.
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Keneth
7 months ago
Hmm, I'm a little unsure about this one. The options seem pretty similar, so I'll need to read through them carefully and think about the context of the question to make the best choice.
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Albina
7 months ago
I'm a bit confused by this one. The wording is a bit technical, and I'm not sure I fully understand the implications of the VMM resolution and the lack of Cisco Discovery Protocol. I'll need to re-read the question carefully.
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Chuck
7 months ago
I feel pretty confident about this one. The JSON structure in Option C looks like it would display all six values correctly in the OmniScript. I'll mark that as my final answer.
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Lai
11 months ago
This question is like a game of 'Guess the Right Answer' with a side of 'Guess the Secret Handshake'.
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Christa
11 months ago
Wait, hold up! Do I really need to convert that DataFrame to a CSV file before getting inferences from SageMaker? Sounds like a lot of extra work to me.
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Youlanda
10 months ago
C: Yeah, converting to a CSV file is not necessary. Just use the SageMaker Spark Library for training and hosting the model.
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Jacquelyne
10 months ago
B: Just use the appropriate estimator from the SageMaker Spark Library to train a model and get inferences.
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Ashley
11 months ago
A: No, you don't need to convert the DataFrame to a CSV file. You can use the sageMakerModel.transform method directly.
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Tegan
12 months ago
Hmm, this question is like a puzzle within a puzzle. I better not forget to compress that data and upload it to S3 before training the model.
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Annamaria
11 months ago
A: D) Compress the training data into a ZIP file and upload it to a pre-defined Amazon S3 bucket.
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Pauline
11 months ago
B: C) Use the appropriate estimator from the SageMaker Spark Library to train a model.
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Marlon
11 months ago
A: B) Install the SageMaker Spark library in the Spark environment.
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Lemuel
12 months ago
Alright, time to put on my machine learning hat and integrate that Spark app with SageMaker. B, C, and D sound like the way to go.
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Diane
10 months ago
D) Compress the training data into a ZIP file and upload it to a pre-defined Amazon S3 bucket.
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Nickole
10 months ago
C) Use the appropriate estimator from the SageMaker Spark Library to train a model.
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Audrie
10 months ago
B) Install the SageMaker Spark library in the Spark environment.
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Lauran
10 months ago
D) Compress the training data into a ZIP file and upload it to a pre-defined Amazon S3 bucket.
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Misty
10 months ago
C) Use the appropriate estimator from the SageMaker Spark Library to train a model.
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Alesia
10 months ago
B) Install the SageMaker Spark library in the Spark environment.
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Vinnie
1 year ago
Whoa, this question is a real brain-teaser! I better download that AWS SDK and get crackin' on those SageMaker Spark libraries.
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Carri
11 months ago
C) Use the appropriate estimator from the SageMaker Spark Library to train a model.
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Josue
11 months ago
B) Install the SageMaker Spark library in the Spark environment.
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Susana
11 months ago
A) Download the AWS SDK for the Spark environment
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Gladys
1 year ago
In addition to that, compressing the training data into a ZIP file and uploading it to an Amazon S3 bucket is necessary for integration.
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Beckie
1 year ago
I agree with Trina, using the appropriate estimator from the SageMaker Spark Library to train a model is also important.
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Trina
1 year ago
I think the Specialist should install the SageMaker Spark library in the Spark environment.
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