Differential Privacy + Federated Learning Explained (+ Tutorial) | #AI101

The video discusses privacy concerns in AI, focusing on Differential Privacy and Federated Learning. Differential Privacy involves adding noise to data to protect individual identities, while Federated Learning trains models across separate data sets without sharing data. The video includes a coding tutorial using Google Collab to experiment with these privacy techniques.

How does Federated Learning differ from Differential Privacy in terms of data handling?

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What are the benefits of using Federated Learning for voice recognition systems like Siri?

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How can individuals experiment with Differential Privacy and Federated Learning at home?

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