Protecting Sensitive Data using Differential Privacy

Using data for machine learning and analytics can potentially expose private data.  How can we leverage data while ensuring that private information remains private? In this session, we'll discuss how differential privacy can be used to preserve privacy.  We'll demonstrate how you can use newly released open source system, WhiteNoise, to put DP into your applications.

Learn More: 

• Azure Machine Learning How To
• Whitenoise Paper
• Open Differential Privacy

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