Question 1

Which of the following represents the CORRECT statement about AWS DeepRacer?

Options :

A : AWS DeepRacer car is based on a model that uses a supervised learning ML algorithm

B : The AWS DeepRacer vehicle is a Wi-Fi enabled, physical vehicle that can drive itself on a physical track

C : AWS DeepRacer vehicle is only a virtual vehicle running on AWS DeepRacer simulator

D : You need an AWS DeepRacer car to use the AWS DeepRacer simulator

Answer: B

Question 2

A company needs to extract handwritten words and letters from scanned documents. Which ML-powered AWS service is the right fit for this requirement?

Options :

A : Amazon Textract

B : Amazon Transcribe

C : Amazon Rekognition

D : Amazon Kendra

Answer: A

Question 3

A company wants a unified search solution that can connect the company's multiple data repositories, third-party document repositories, and FAQs to create a new search experience so that the employees can efficiently find the right answers for their queries.

Which Machine Learning powered AWS service offers these search features?

Options :

A : Amazon Textract

B : Amazon SageMaker Data Wrangler

C : Amazon Comprehend

D : Amazon Kendra

Answer: D

Question 4

A retail company is exploring the use of generative AI to improve its customer experience by personalizing recommendations and automating product descriptions. The company is interested in leveraging pre-built, high-performing Foundation Models (FMs) to accelerate development but also needs the ability to customize these models with its proprietary data to meet specific business needs. The company is seeking an AWS service that not only provides access to a variety of Foundation Models but also offers the option to privately fine-tune and customize these models for their unique use case.Which AWS service/feature offers a choice of high-performing Foundation Models (FMs) and the ability to privately customize the FMs with your data?

Options :

A : Amazon Q Developer

B : Amazon Q in QuickSight

C : AWS Inferentia

D : Amazon Bedrock

Answer: D

Question 5

How would you differentiate between K-Means and K-Nearest Neighbors (KNN) algorithms in machine learning?

Options :

A : K-Means is primarily used for regression tasks, while KNN is used for reducing the dimensionality of data

B : K-Means is an unsupervised learning algorithm used for clustering data points into groups, while KNN is a supervised learning algorithm used for classifying data points based on their proximity to labeled examples

C : K-Means is a supervised learning algorithm used for classification, while KNN is an unsupervised learning algorithm used for clustering

D : K-Means requires labeled data to form clusters, whereas KNN does not use labeled data for making predictions

Answer: B

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