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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