apunkt/ai-privacy-toolkit
1
0
Fork 0
mirror of https://github.com/IBM/ai-privacy-toolkit.git synced 2026-06-02 14:45:13 +02:00
Code Issues Projects Releases Packages Wiki Activity Actions

Increase version to 0.2.0 (#74)

Browse source 
* Remove tensorflow dependency if not using keras model
* Remove xgboost dependency if not using xgboost model
* Documentation updates

Signed-off-by: abigailt <abigailt@il.ibm.com>
This commit is contained in:
abigailgold 2023-05-08 12:50:55 +03:00 • committed by abigailt
parent 98a7a078bb
commit 04d8df8091
25 changed files with 306 additions and 152 deletions
Download patch file Download diff file Expand all files Collapse all files

2
docs/index.rst
View file

@ -18,6 +18,8 @@ minimization principle in GDPR for ML models. It enables to reduce the amount of
personal data needed to perform predictions with a machine learning model, while still enabling the model
to make accurate predictions. This is done by by removing or generalizing some of the input features.
The dataset risk assessment module implements a tool for privacy assessment of synthetic datasets that are to be used in AI model training.
.. toctree::
:maxdepth: 2
:caption: Getting Started: