Practice Questions

Question 1

A company is developing a recommendation system for an online shopping platform. The goal is for the system to enhance suggestions based on user behavior and feedback over time. Which AI learning strategy enables this adaptive improvement?

1) Unsupervised learning to identify patterns in user preferences.
2) Supervised learning with a fixed dataset of past purchases and ratings.
3) Supervised learning with an evolving dataset of customer interactions.
4) Reinforcement learning with rewards based on customer engagement metrics.

Answer 1

4) Reinforcement learning with rewards based on customer engagement metrics.

Question 2

A company has developed a classification model to identify whether emails are spam or not. After training and validating the model, the company wants to evaluate its performance using a metric that represents the overall proportion of correct predictions. Which evaluation metric should the company use?

1) R^2 (R Squared)
2) Root Mean Squared Error (RMSE)
3) F1 Score
4) Accuracy

Answer 2

4) Accuracy

Question 3

A company is developing a sentiment analysis tool to access customer feedback from various sources. The goal is to automatically analyze text data and derive insights about customer emotions and key themes. Which solution meets these requirements?

1) Amazon Textract
2) Amazon Comprehend
3) Amazon SageMaker
4) Amazon Rekognition

Answer 3

2) Amazon Comprehend

Question 4

Which Amazon SageMaker service is designed to streamline the data preparation process by allowing users to visually clean and transform data for machine learning?

1) Amazon SageMaker Feature Store
2) Amazon SageMaker Clarify
3) Amazon SageMaker Pipelines
4) Amazon SageMaker Data Wrangler

Answer 4

4) Amazon SageMaker Data Wrangler