AWS AWS Machine Learning and AI Services 5 — Questions and Answers
Question 1: What is the function of AWS DeepRacer?
- A physical and simulated racing car platform for learning reinforcement learning (Correct answer)
- A GPU-optimized EC2 instance for deep learning workloads
- A service for accelerating neural network inference
- A framework for distributed deep learning training
Correct answer: A physical and simulated racing car platform for learning reinforcement learning
AWS DeepRacer is a 1/18th scale autonomous race car and cloud-based 3D racing simulator designed to help developers learn reinforcement learning hands-on.
Question 2: Which SageMaker capability automates the end-to-end process of building, training, and tuning an ML model for a given dataset?
- SageMaker Autopilot (Correct answer)
- SageMaker Pipelines
- SageMaker JumpStart
- SageMaker Canvas
Correct answer: SageMaker Autopilot
SageMaker Autopilot automatically explores different algorithms and configurations to find the best model for your data, providing full visibility into the process.
Question 3: Amazon Comprehend Medical is specifically designed to extract information from which type of data?
- Clinical notes and medical records (Correct answer)
- Pharmaceutical research papers only
- Medical device sensor readings
- Insurance billing codes
Correct answer: Clinical notes and medical records
Amazon Comprehend Medical uses NLP to extract medical information such as diagnoses, medications, and dosages from unstructured clinical text.
Question 4: Which deployment option in SageMaker is designed for low-latency, high-throughput real-time predictions on single data points?
- Real-time inference endpoints (Correct answer)
- Batch Transform
- Asynchronous inference
- Serverless inference
Correct answer: Real-time inference endpoints
SageMaker real-time inference endpoints provide persistent, low-latency endpoints suitable for synchronous, single-record predictions.
Question 5: What is the primary use case for Amazon Lex?
- Building conversational interfaces using voice and text (Correct answer)
- Performing sentiment analysis on customer reviews
- Transcribing audio files to text
- Translating conversations between languages in real time
Correct answer: Building conversational interfaces using voice and text
Amazon Lex provides automatic speech recognition and natural language understanding to build chatbots and virtual assistants for voice and text.
Question 6: A data scientist needs to explain why a SageMaker model made a specific prediction and check for bias in training data. Which tool should they use?
- SageMaker Clarify (Correct answer)
- SageMaker Debugger
- SageMaker Model Monitor
- SageMaker Experiments
Correct answer: SageMaker Clarify
SageMaker Clarify provides tools for bias detection in datasets and models, and generates feature attribution explanations using SHAP values.
Question 7: Which AWS service provides pre-trained, customizable foundation models through a serverless API without requiring infrastructure management?
- Amazon Bedrock (Correct answer)
- Amazon SageMaker JumpStart
- AWS Inferentia
- Amazon Titan
Correct answer: Amazon Bedrock
Amazon Bedrock provides access to foundation models from AWS and third-party providers via a serverless API, with no infrastructure to manage.
AWS AWS Machine Learning and AI Services 5
What is the function of AWS DeepRacer?