Practical understanding of the privacy-utility trade-off.
The Privacy Utility Trade-Off
Overview
Dive into the nuances of the privacy versus utility trade-off in data analysis with AGENT in this practical tutorial. Understand the implications of selecting different levels of Epsilon and how it influences the accuracy of your results.
You'll learn how to create mock datasets of various sizes, apply differential privacy mechanisms with different Epsilon values, and measure performance using root mean squared errors and relative errors. This tutorial demonstrates the direct impact of noise on data utility and highlights how dataset size and mechanism choice can affect performance outcomes.
Included in this video
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Creating mock datasets and applying differential privacy mechanisms.
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Measuring performance with root mean squared and relative errors.
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Visualising the impact of Epsilon on the accuracy of data analysis.