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What are best practices for Privacy-Preserving Machine Learning

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When working with Privacy-Preserving Machine Learning, start with a clear goal, test on real data early, keep the approach as simple as possible at first, and follow established practices from the AI community rather than guessing.
Real-world example A hospital uses privacy preserving machine learning techniques to train a diagnostic model without ever centralizing patients' raw medical records in one place.

Common follow-ups: What is AI Security & Adversarial Attacks, How is Privacy-Preserving Machine Learning evaluated in practice, What tools are commonly used for Privacy-Preserving Machine Learning

AI Security & Adversarial Attacks topics: Introduction to AI Security Adversarial Examples & Attacks Data Poisoning Attacks
All 7 Privacy-Preserving Machine Learning questions