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Exam AWS Certified Machine Learning - Specialty topic 1 question 128 discussion

Exam question from Amazon's AWS Certified Machine Learning - Specialty

Question #: 128
Topic #: 1

[All AWS Certified Machine Learning - Specialty Questions]

A company is using Amazon Textract to extract textual data from thousands of scanned text-heavy legal documents daily. The company uses this information to process loan applications automatically. Some of the documents fail business validation and are returned to human reviewers, who investigate the errors. This activity increases the time to process the loan applications.
What should the company do to reduce the processing time of loan applications?

A. Configure Amazon Textract to route low-confidence predictions to Amazon SageMaker Ground Truth. Perform a manual review on those words before performing a business validation.
B. Use an Amazon Textract synchronous operation instead of an asynchronous operation.
C. Configure Amazon Textract to route low-confidence predictions to Amazon Augmented AI (Amazon A2I). Perform a manual review on those words before performing a business validation.
D. Use Amazon Rekognition's feature to detect text in an image to extract the data from scanned images. Use this information to process the loan applications.

Show Suggested Answer

Suggested Answer: C 🗳️

by [deleted] at Feb. 6, 2021, 12:58 a.m.

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Highly Voted 2 years, 2 months ago

I agree with C, given we are evaluating model inferences (predictions). See https://aws.amazon.com/augmented-ai/ and https://aws.amazon.com/blogs/machine-learning/automated-monitoring-of-your-machine-learning-models-with-amazon-sagemaker-model-monitor-and-sending-predictions-to-human-review-workflows-using-amazon-a2i/

upvoted 21 times

Dr_Kiko

2 years, 1 month ago

yeap, it literally says it there Loan or mortgage applications, tax forms, and many other financial documents contain millions of data points which need to be processed and extracted quickly and effectively. Using Amazon Textract and Amazon A2I you can extract critical data from these forms

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alp_ileri

Most Recent 9 months, 3 weeks ago

why not a?

upvoted 1 times

ZSun

8 months, 1 week ago

the differences rely on the function of these two service. Ground Truth is used for "labeling" typically, text or image label: if the service cannot automatically label the data, it send to ground truth and wait for human to label it. but A2I is for validate prediction. The model already predict the results and human then add views to it.

upvoted 5 times

ZSun

7 months, 3 weeks ago

https://docs.aws.amazon.com/textract/latest/dg/a2i-textract.html https://aws.amazon.com/blogs/machine-learning/using-amazon-textract-with-amazon-augmented-ai-for-processing-critical-documents/

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alp_ileri

9 months, 3 weeks ago

i think ground truth can do same task instead of Augmented AI

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Valcilio

9 months, 3 weeks ago

Selected Answer: C

The answer is C, Augmented AI is made for review ML predictions!

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AjoseO

10 months, 2 weeks ago

Selected Answer: C

By routing the low-confidence predictions to Amazon Augmented AI, the company can reduce the time to process the loan applications by leveraging human intelligence to review and validate the predictions. This way, the company can quickly address any errors or mistakes that Amazon Textract might make, reducing the time to process loan applications.

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Juka3lj

2 years, 2 months ago

correct is C

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