Marqueguard is a social media monitoring company headquartered in Brighton, England.
Marqueguard sells three different products: Analytics, Audiences, and Insights.
Marqueguard Analytics is a "self-serveapplication" or software as a service, which archives social media data in order to provide companies with information and the means to track specific segments to analyze their brands' online presence. The tool's coverage includes blogs, news sites, forums, videos, reviews, images and social networks such as Twitter and Facebook.
Users can search data by using Text and Image Search, and use charting, categorization, sentiment analysis and other features to provide further information and analysis.
Marqueguard has access to over 80 million sources. Marqueguard has a large team of data scientists and want to provide fully managed machine learning service data scientists and developers can quickly and easily build and train machine learning models, and then directly deploy them into a production-ready hosted environment. What service can provide this capability? select 1 option.
Click on the arrows to vote for the correct answer
A. B. C. D.Answer : D.
Option A is incorrect - Amazon Comprehend uses natural language processing (NLP) to extract insights about the content of documents.
Amazon Comprehend processes any text file in UTF-8 format.
It develops insights by recognizing the entities, key phrases, language, sentiments, and other common elements in a document.
Use Amazon Comprehend to create new products based on understanding the structure of documents.
For example, using Amazon Comprehend you can search social networking feeds for mentions of products or scan an entire document repository for key phrases.
https://docs.aws.amazon.com/comprehend/latest/dg/what-is.htmlOption B is incorrect - 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 objects, people, text, scenes, and activities.
It can detect any inappropriate content as well.
Amazon Rekognition also provides highly accurate facial analysis and facial recognition.
You can detect, analyze, and compare faces for a wide variety of use cases, including user verification, cataloging, people counting, and public safety.
https://docs.aws.amazon.com/rekognition/latest/dg/what-is.htmlOption C is incorrect -Amazon Polly is a cloud service that converts text into lifelike speech.
You can use Amazon Polly to develop applications that increase engagement and accessibility.
Amazon Polly supports multiple languages and includes a variety of lifelike voices, so you can build speech-enabled applications that work in multiple locations and use the ideal voice for your customers.
With Amazon Polly, you only pay for the text you synthesize.
You can also cache and replay Amazon Polly's generated speech at no additional cost.
https://docs.aws.amazon.com/polly/latest/dg/what-is.htmlOption D is correct - Amazon SageMaker is a fully managed machine learning service.
With Amazon SageMaker, data scientists and developers can quickly and easily build and train machine learning models, and then directly deploy them into a production-readyhosted environment.
It provides an integrated Jupyter authoring notebook instance for easy access to your data sources for exploration and analysis, so you don't have to manage servers.
It also provides common machine learning algorithms that are optimized to run efficiently against extremely large data in a distributed environment
https://docs.aws.amazon.com/sagemaker/latest/dg/whatis.htmlThe service that can provide Marqueguard with fully managed machine learning capabilities to quickly and easily build and deploy machine learning models into a production-ready environment is Amazon SageMaker.
Amazon SageMaker is a fully managed service that provides data scientists and developers with the ability to quickly build, train, and deploy machine learning models. With SageMaker, users can build and train machine learning models using a range of popular open-source frameworks like TensorFlow, Apache MXNet, PyTorch, and more.
Amazon SageMaker allows users to build custom machine learning models using their own data, or use SageMaker's pre-built algorithms to get started quickly. Users can also train models using large datasets distributed across multiple instances, or use SageMaker's built-in auto-scaling capabilities to automatically adjust resources based on demand.
SageMaker also makes it easy to deploy machine learning models into production environments, with built-in support for popular deployment options like Docker containers and Kubernetes. Once deployed, SageMaker provides a fully managed hosting environment that scales automatically based on demand.
In summary, Amazon SageMaker is the service that can provide Marqueguard with fully managed machine learning capabilities to build and deploy machine learning models into a production-ready environment.