Google Cloud Professional Data Engineer — Question 26

Business owners at your company have given you a database of bank transactions. Each row contains the user ID, transaction type, transaction location, and transaction amount. They ask you to investigate what type of machine learning can be applied to the data. Which three machine learning applications can you use? (Choose three.)

Answer options

• A. Supervised learning to determine which transactions are most likely to be fraudulent.
• B. Unsupervised learning to determine which transactions are most likely to be fraudulent.
• C. Clustering to divide the transactions into N categories based on feature similarity.
• D. Supervised learning to predict the location of a transaction.
• E. Reinforcement learning to predict the location of a transaction.
• F. Unsupervised learning to predict the location of a transaction.

Correct answer: B, C, D

Explanation

The correct answers are B, C, and D. Unsupervised learning can help identify patterns in data without labeled outcomes, making it suitable for detecting potential fraud (B). Clustering (C) is effective for grouping transactions based on similarities. Supervised learning (D) can be used to predict outcomes like transaction location based on labeled data. The other options either misapply the concepts or are not suited for the given dataset.