You work as a machine learning specialist for an online news organization. Your company is implementing a crowd-sourced news feature that will allow subscribers to upload their own news stories complete with images. You have been tasked with building and deploying a machine learning model that alerts adult content in an image uploaded by a subscriber. Which option describes the best data preparation and implementation of your machine learning hosted inference?

Answer options:

A.Use the Semantic Segmentation SageMaker built-in algorithm and code your application to query the deployed endpoint providing an image in the image/png content type.
B.Use the Object2Vec SageMaker built-in algorithm and code your application to query the deployed endpoint providing an image in the application/jsonlines content type.
C.Use the Image Classification SageMaker built-in algorithm and code your application to query the deployed endpoint providing an image in the application/x-recordio content type.
D.Use the Image Classification SageMaker built-in algorithm and code your application to query the deployed endpoint providing an image in the application/x-image content type.

Correct Answer: D
Option A is incorrect. The Semantic Segmentation SageMaker built-in algorithm is used to provide a fine-grained, pixel-level approach to developing computer vision applications. It would function poorly as a model to detect adult content in an image.
Option B is incorrect. The Object2Vec SageMaker built-in algorithm is used to compute the nearest neighbors of objects and visualize natural clusters of related objects in low-dimensional space. For example, common use cases include identifying duplicate support tickets or finding the correct routing based on the similarity of text in the tickets. It would function poorly as a model to detect adult content in an image.
Option C is incorrect. The Image Classification SageMaker built-in algorithm is the correct algorithm for using as an inference engine to detect adult content in an uploaded image. However, an Image Classification deployed endpoint doesn’t take inference requests in the application/x-recordio content type.
Option D is correct. The Image Classification SageMaker built-in algorithm is the correct algorithm for using as an inference engine to detect adult content in an uploaded image. Also, an Image Classification deployed endpoint takes inference requests in the application/x-image content type.
References:
Please see the Amazon SageMaker developer guide titled Use Amazon SageMaker Built-in Algorithms (https://docs.aws.amazon.com/sagemaker/latest/dg/algos.html),
The Amazon SageMaker developer guide titled Semantic Segmentation Algorithm (https://docs.aws.amazon.com/sagemaker/latest/dg/semantic-segmentation.html),
The Amazon SageMaker developer guide titled Object2Vec Algorithm (https://docs.aws.amazon.com/sagemaker/latest/dg/object2vec.html),
The Amazon SageMaker developer guide titled Image Classification Algorithm (https://docs.aws.amazon.com/sagemaker/latest/dg/image-classification.html),
The Amazon SageMaker developer guide titled Common Data Formats for Inference (https://docs.aws.amazon.com/sagemaker/latest/dg/cdf-inference.html)