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Epsilon (ϵ): the magic number

One of differential privacy's great successes is that it reduces the essential trade-off in privacy-preserving data analysis, accuracy versus privacy, to a single number.

In differential privacy systems, if the value of epsilon (\(\epsilon\)) is a small number, what does it means for the resulting data?

This exercise is part of the course

Data Privacy and Anonymization in Python

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