Amazon MLS-C01 Exam - Topic 5 Question 73 Discussion

Actual exam question for Amazon's MLS-C01 exam

Question #: 73
Topic #: 5

A wildlife research company has a set of images of lions and cheetahs. The company created a dataset of the images. The company labeled each image with a binary label that indicates whether an image contains a lion or cheetah. The company wants to train a model to identify whether new images contain a lion or cheetah.

.... Dh Amazon SageMaker algorithm will meet this requirement?

AXGBoost

BImage Classification - TensorFlow

CObject Detection - TensorFlow

DSemantic segmentation - MXNet

Show Suggested Answer

Suggested Answer: A

by Maryann at Mar 29, 2023, 12:01 PM

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Kiley

7 months ago

Definitely Image Classification - TensorFlow, no doubt about it!

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Craig

7 months ago

Wait, why not use Semantic segmentation? Seems like a stretch.

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Harris

7 months ago

XGBoost? Really? That seems off for image data.

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Major

8 months ago

I think Object Detection - TensorFlow could work too.

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Adolph

8 months ago

Image Classification - TensorFlow is perfect for this!

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Alona

8 months ago

Object detection seems like it might be overkill since we just need to classify the images, but I'm not completely confident about that.

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Svetlana

8 months ago

I practiced a similar question, and I think the image classification option would be the most straightforward for identifying lions and cheetahs.

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Lea

8 months ago

I'm not entirely sure, but I feel like XGBoost is more for structured data rather than images.

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Chandra

8 months ago

I remember studying image classification models, and I think TensorFlow is a good choice for this task.

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Lezlie

8 months ago

This is a tricky one. I'll need to draw on my knowledge of network concepts to figure out which statement doesn't align with how SAPs work.

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Nenita

8 months ago

This looks like a straightforward question. I'd use preg_quote() and addslashes() to escape special characters in user input before using it in a regular expression.

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Lynelle

8 months ago

The Microsoft Software Installer (MSI) option seems promising, but I'm not completely confident. I'll have to review my notes.

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Rikki

1 year ago

I wonder if the company has considered training the model to identify the animals' species by their roars or purrs. Just a thought - a real 'lion's share' of insight there!

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Donte

1 year ago

Hmm, I'm going to have to go with option C, Object Detection - TensorFlow. Identifying the exact location of the animals in the image could be useful for the research company.

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Cyril

12 months ago

Yes, Object Detection - TensorFlow would definitely help in accurately identifying whether the images contain lions or cheetahs.

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Leatha

12 months ago

Yes, Object Detection - TensorFlow could definitely help in accurately identifying whether an image contains a lion or cheetah.

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Camellia

12 months ago

Agreed, being able to detect the exact location of the animals in the images would be very beneficial for the research company.

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Marta

12 months ago

Agreed, being able to detect the exact location of the animals in the images would be very beneficial.

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Jeffrey

1 year ago

I think option C, Object Detection - TensorFlow, would be the best choice for this task.

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Tien

1 year ago

I think option C, Object Detection - TensorFlow, would be the best choice for this task.

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Lisandra

1 year ago

Semantic segmentation? Seriously, D? We're talking about identifying lions and cheetahs, not pixel-level classification. Let's keep it simple and go with B or C.

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Wei

12 months ago

B) Image Classification - TensorFlow

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Paola

12 months ago

C) Object Detection - TensorFlow

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Louvenia

12 months ago

B) Image Classification - TensorFlow

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Shaquana

12 months ago

B) Image Classification - TensorFlow

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Leonard

1 year ago

C) Object Detection - TensorFlow

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Wei

1 year ago

B) Image Classification - TensorFlow

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Truman

1 year ago

I'm not convinced by the XGBoost option, A. That's more for structured data, not images. I'd stick with the TensorFlow-based solutions, B or C.

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Veronica

1 year ago

This looks like a classic image classification problem, so I'd go with option B, Image Classification - TensorFlow. It's a well-established algorithm for this kind of task.

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