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PROFESSIONAL-MACHINE-LEARNING-ENGINEER · Question #118
You are an ML engineer at a bank that has a mobile application. Management has asked you to build an ML-based biometric authentication for the app that verifies a customer's identity based on their fi
The correct answer is B. Federated learning. With federated learning, all the data is collected, and the model is trained with algorithms across multiple decentralized edge devices such as cell phones or websites, without exchanging them. (Journey to Become a Google Cloud Machine Learning Engineer: Build the mind and hand o
Submitted by kim_seoul· Apr 18, 2026ML model development
Question
You are an ML engineer at a bank that has a mobile application. Management has asked you to build an ML-based biometric authentication for the app that verifies a customer's identity based on their fingerprint. Fingerprints are considered highly sensitive personal information and cannot be downloaded and stored into the bank databases. Which learning strategy should you recommend to train and deploy this ML mode?
Options
- AData Loss Prevention API
- BFederated learning
- CMD5 to encrypt data
- DDifferential privacy
How the community answered
(28 responses)- A4% (1)
- B79% (22)
- C7% (2)
- D11% (3)
Explanation
With federated learning, all the data is collected, and the model is trained with algorithms across multiple decentralized edge devices such as cell phones or websites, without exchanging them. (Journey to Become a Google Cloud Machine Learning Engineer: Build the mind and hand of a Google Certified ML professional)
Topics
#Federated Learning#Privacy-preserving ML#Sensitive Data#Biometric Authentication
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