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Question 184 - MLS-C01 discussion

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An agricultural company is interested in using machine learning to detect specific types of weeds in a 100-acre grassland field. Currently, the company uses tractor-mounted cameras to capture multiple images of the field as 10 10 grids. The company also has a large training dataset that consists of annotated images of popular weed classes like broadleaf and non-broadleaf docks.

The company wants to build a weed detection model that will detect specific types of weeds and the location of each type within the field. Once the model is ready, it will be hosted on Amazon SageMaker endpoints. The model will perform real-time inferencing using the images captured by the cameras.

Which approach should a Machine Learning Specialist take to obtain accurate predictions?

A.
Prepare the images in RecordIO format and upload them to Amazon S3. Use Amazon SageMaker to train, test, and validate the model using an image classification algorithm to categorize images into various weed classes.
Answers
A.
Prepare the images in RecordIO format and upload them to Amazon S3. Use Amazon SageMaker to train, test, and validate the model using an image classification algorithm to categorize images into various weed classes.
B.
Prepare the images in Apache Parquet format and upload them to Amazon S3. Use Amazon SageMaker to train, test, and validate the model using an object-detection single-shot multibox detector (SSD) algorithm.
Answers
B.
Prepare the images in Apache Parquet format and upload them to Amazon S3. Use Amazon SageMaker to train, test, and validate the model using an object-detection single-shot multibox detector (SSD) algorithm.
C.
Prepare the images in RecordIO format and upload them to Amazon S3. Use Amazon SageMaker to train, test, and validate the model using an object-detection single-shot multibox detector (SSD) algorithm.
Answers
C.
Prepare the images in RecordIO format and upload them to Amazon S3. Use Amazon SageMaker to train, test, and validate the model using an object-detection single-shot multibox detector (SSD) algorithm.
D.
Prepare the images in Apache Parquet format and upload them to Amazon S3. Use Amazon SageMaker to train, test, and validate the model using an image classification algorithm to categorize images into various weed classes.
Answers
D.
Prepare the images in Apache Parquet format and upload them to Amazon S3. Use Amazon SageMaker to train, test, and validate the model using an image classification algorithm to categorize images into various weed classes.
Suggested answer: C

Explanation:

The problem of detecting specific types of weeds and their location within the field is an example of object detection, which is a type of machine learning model that identifies and localizes objects in an image. Amazon SageMaker provides a built-in object detection algorithm that uses a single-shot multibox detector (SSD) to perform real-time inference on streaming images. The SSD algorithm can handle multiple objects of varying sizes and scales in an image, and generate bounding boxes and scores for each object category. Therefore, option C is the best approach to obtain accurate predictions.

Option A is incorrect because image classification is a type of machine learning model that assigns a label to an image based on predefined categories. Image classification is not suitable for localizing objects within an image, as it does not provide bounding boxes or scores for each object. Option B is incorrect because Apache Parquet is a columnar storage format that is optimized for analytical queries. Apache Parquet is not suitable for storing images, as it does not preserve the spatial information of the pixels. Option D is incorrect because it combines the wrong format (Apache Parquet) and the wrong algorithm (image classification) for the given problem, as explained in options A and B.

References:

Object Detection algorithm now available in Amazon SageMaker

Image classification and object detection using Amazon Rekognition Custom Labels and Amazon SageMaker JumpStart

Object Detection with Amazon SageMaker - W3Schools aws-samples/amazon-sagemaker-tensorflow-object-detection-api

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asked 16/09/2024
Dennis Valencia
34 questions
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