New Tutorial: Demonstrate DP on DataWarehouse for #300 #346
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Koukyosyumei
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run-clang-format.py
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| @@ -143,7 +144,8 @@ def run_clang_format_diff_wrapper(args, file): | |||
| except DiffError: | |||
| raise | |||
| except Exception as e: | |||
| raise UnexpectedError("{}: {}: {}".format(file, e.__class__.__name__, e), e) | |||
| raise UnexpectedError("{}: {}: {}".format( | |||
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Can we use f-strings here?
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It's not what I intended, and I reset the commit
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| expect_near = lambda expected, actual, tol: ( | ||
| def expect_near(expected, actual, tol): return ( |
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is there a reason to move from lambda to this new implementation?
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It's not what I intended, and I reset the commit
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@chinmayshah99 |
chinmayshah99
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Type: New Feature ➕
chinmayshah99
added
Status: Stale 🍞
Description
This PR aims to close #300.
Although the label of #300 is "status in progress", it seems that no one is working on this issue.
This notebook consists of two parts. The first part shows how differential privacy works under the assumption that the attacker already knows almost all of the data except one record. In the second one, the attacker tries to identify one person, and the defender uses differential privacy to avoid this.
It is the first PR for me to this excellent project, so if I misunderstand something, please correct me!
Affected Dependencies
no
How has this been tested?
jupyter lab
Checklist