Topic 1 Question 107
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?
Data Loss Prevention API
Federated learning
MD5 to encrypt data
Differential privacy
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コメント(8)
- 正解だと思う選択肢: B
B 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)
👍 5hiromi2022/12/20 - 正解だと思う選択肢: B
I think the giveaway is in the question "Which learning strategy.."... Federated Learning seems to be the only one !
👍 2Yajnas_arpohc2023/03/20 - 正解だと思う選択肢: B
Federated Learning enables mobile phones to collaboratively learn a shared prediction model while keeping all the training data on device. https://ai.googleblog.com/2017/04/federated-learning-collaborative.html
👍 1mil_spyro2022/12/13
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