Machine Learning

Question 1

What are the benefits of using Amazon Rekognition with image files?

1. Can be used to resize images
2. Can be used to identify objects in an image
3. Can be used to transcode audio
4. Can help with image compression

Answer 1

2. Can be used to identify objects in an image

Rekognition Image is a deep learning powered image recognition service that detects objects, scenes, and faces; extracts text; recognizes celebrities; and identifies inappropriate content in images. It also allows you to search and compare faces.

• Can be used to resize images is incorrect. You cannot use Rekognition to resize images.
• Can be used to transcode audio is incorrect. You should use the Elastic Transcoder service to transcode audio.
• Can help with image compression is incorrect. You cannot use Rekognition to compress images.

Reference:
Amazon Rekognition Image

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Question 2

What fully managed AWS service allows users to bring their own machine learning algorithms?

1. Amazon Forecast
2. AWS Artifact
3. AWS Data Pipeline
4. Amazon SageMaker

Answer 2

4. Amazon SageMaker

Amazon SageMaker is a managed Machine Learning service. With Amazon SageMaker, you can package your own algorithms that can then be trained and deployed in the SageMaker environment.

• AWS Artifact is incorrect. AWS Artifact is your go-to, central resource for compliance-related information. It has nothing to do with Machine Learning.
• AWS Data Pipeline is incorrect. AWS Data Pipeline is a web service that helps you reliably process and move data between different AWS compute and storage services, as well as on-premises data sources, at specified intervals. It does not use Machine Learning.
• Amazon Forecast is incorrect. Amazon Forecast is a time- series forecasting service based on machine learning (ML) and built for business metrics analysis. Although it is based on Machine Learning, it does not allow you to bring your own algorithms,

Reference:
Amazon SageMaker

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Question 3

Which AWS service uses machine learning to enable natural language search capabilities in your applications, making it easier to find the precise answer to your questions within a large set of documents?

1. Amazon Comprehend
2. Amazon Lex
3. Amazon Kendra
4. Amazon ElasticSearch

Answer 3

3. Amazon Kendra

Amazon Kendra is the correct answer because it is a highly accurate and easy-to-use enterprise search service powered by machine learning. It provides natural language search capabilities, meaning that users can ask questions using everyday language and Kendra will find the precise answers in the document set.

• Amazon Comprehend is incorrect as it is a natural language processing (NLP) service that uses machine learning to analyze text documents, but it does not offer search capabilities to find precise answers to natural language queries across a large set of documents.
• Amazon Lex is incorrect because it is a service for building conversational interfaces using voice and text, rather than a search service designed to find specific answers in a large document set using natural language queries.
• Amazon ElasticSearch is incorrect because, even though it is a search and analytics engine, it does not natively offer the natural language processing and machine learning capabilities required to find precise answers to natural language questions in a set of documents; it is generally used for log analytics and other application monitoring purposes.

Reference:
Amazon Kendra

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Question 4

Which AWS service enables developers and data scientists to build, train, and deploy machine learning models?

1. Amazon Rekognition
2. Amazon Comprehend
3. Amazon SageMaker
4. Amazon MQ

Answer 4

3. Amazon SageMaker

Amazon SageMaker is a fully-managed platform that enables developers and data scientists to quickly and easily build, train, and deploy machine learning models at any scale. Amazon SageMaker removes all the barriers that typically slow down developers who want to use machine learning.

• Amazon Rekognition is incorrect. Amazon Rekognition makes it easy to add image and video analysis to your applications.
• Amazon Comprehend is incorrect. Amazon Comprehend is a natural language processing (NLP) service that uses machine learning to find insights and relationships in text
• Amazon MQ is incorrect. Amazon MQ is a managed message broker service for Apache ActiveMQ that makes it easy to set up and operate message brokers in the cloud.

Reference:
Amazon SageMaker

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Question 5

A company is looking to develop a conversational chatbot that can interact dynamically with its customers through a natural language interface.

Which AWS service should be utilized to facilitate this?

1. Amazon Lex
2. Amazon Transcribe
3. Amazon Comprehend
4. Amazon Textract

Answer 5

1. Amazon Lex

Amazon Lex is the correct answer as it is an AWS service specifically designed to build conversational interfaces using voice and text. Leveraging advanced deep learning functionalities, it enables the creation of chatbots that can engage with users naturally.

• Amazon Transcribe is incorrect because while it can convert speech to text, it is not designed to build conversational interfaces; its primary function is to transcribe audio files.
• Amazon Comprehend is incorrect because this service primarily understands the sentiment, language, and entities in a text rather than facilitating conversational interfaces.
• Amazon Textract is incorrect because its focus is on extracting text and data from scanned documents, which does not serve the purpose of creating a conversational chatbot.

Reference:
Amazon Lex - AI Chat Builder

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Question 6

Which feature of Amazon Rekognition can assist with saving time?

1. Identification of objects in images and videos
2. Identification of the language of text in a document
3. Adds automatic speech recognitions (ASR) to applications
4. Provides on-demand access to compliance-related information

Answer 6

1. Identification of objects in images and videos

Amazon Rekognition makes it easy to add image and video analysis to your applications. You just provide an image or video to the Rekognition API, and the service can identify the objects, people, text, scenes, and activities, as well as detect any inappropriate content.

• Identification of the language of text in a document is incorrect. Amazon Comprehend identifies the language of the text; extracts key phrases, places, people, brands, or events; understands how positive or negative the text is; analyzes text using tokenization and parts of speech; and automatically organizes a collection of text files by topic.
• Adds automatic speech recognitions (ASR) to applications is incorrect. Amazon Transcribe is an automatic speech recognition (ASR) service that makes it easy for developers to add speech-to-text capability to their applications
• Provides on-demand access to compliance-related information is incorrect. AWS Artifact is a resource for compliance-related information. It provides on-demand access to AWS’ security and compliance reports and select online agreements

Reference:
Amazon Rekognition

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