Practice Test GeeksAWS Practice Test
← All AWS Flashcard Decks

AWS Machine Learning and AI Services Flashcards

7 cards from real AWS practice questions. Tap to flip, then mark Knew It or Still Learning — missed cards come back until you master them.

Read the first 7 AWS Machine Learning and AI Services flashcards as text

  1. What is Amazon Personalize primarily used for?

    Answer: Creating personalized product and content recommendations

    Amazon Personalize is a fully managed ML service that enables developers to build applications with the same real-time personalized recommendation technology used by Amazon.com.

  2. Which AWS service uses machine learning to identify potentially fraudulent activities?

    Answer: Amazon Fraud Detector

    Amazon Fraud Detector is a fully managed service that uses ML and Amazon's fraud detection expertise to identify potentially fraudulent activities such as online payment fraud.

  3. What is Amazon Textract used for?

    Answer: Automatically extracting text and data from scanned documents

    Amazon Textract automatically extracts text, handwriting, and structured data such as forms and tables from scanned documents and images using ML.

  4. Which AWS service provides neural machine translation of text between languages?

    Answer: Amazon Translate

    Amazon Translate is a neural machine translation service that delivers fast, high-quality, and affordable language translation between many supported languages.

  5. What is AWS DeepRacer primarily designed for?

    Answer: Learning reinforcement learning concepts through an autonomous racing car

    AWS DeepRacer is a fully autonomous 1/18th scale race car designed to help developers learn reinforcement learning by training and racing models on a virtual or physical track.

  6. What is Amazon Kendra used for?

    Answer: Providing intelligent enterprise search powered by machine learning

    Amazon Kendra is an intelligent search service powered by ML that enables organizations to search across various content repositories and receive highly accurate answers.

  7. Which Amazon SageMaker feature helps build highly accurate training datasets by supporting data labeling workflows?

    Answer: Amazon SageMaker Ground Truth

    Amazon SageMaker Ground Truth helps build highly accurate training datasets by providing labeling workflows supported by human annotators or automated labeling.