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Experiments with the Differential Privacy Library on GitHub Diffprivlib

Objective

Experiment with differential privacy using IBM opensourced Differential Privacy Library on GitHub Diffprivlib is a general-purpose library from IBM for experimenting with, investigating and developing applications in, differential privacy. Use diffprivlib if you are looking to experiment with differential privacy Explore the impact of differential privacy on machine learning accuracy using classification and clustering models. One can build your own differential privacy applications, using our extensive collection of mechanisms Diffprivlib supports Python versions 3.6 to 3.8. https://github.com/IBM/differential-privacy-library

Outcomes

Working code and demos of the experiments performed, Contribution to Open Source, Publications/Blogs

Apply by Date

31/10/2020

Applied Teams

2 / 4

Duration

6 months

College

1. Cummins College of Engineering, Pune

2. Vishwakarma Institute of Technology, Pune

Tools-Technologies

Jupyter Python Notebooks, Python

Mentor

Mahesh

Mahesh's comments

Experiment with differential privacy using IBM opensourced Differential Privacy Library on GitHub

Diffprivlib is a general-purpose library from IBM for experimenting with, investigating and developing applications in, differential privacy.

Use diffprivlib if you are looking to experiment with differential privacy Explore the impact of differential privacy on machine learning accuracy using classification and clustering models. One can build your own differential privacy applications, using our extensive collection of mechanisms

Diffprivlib supports Python versions 3.6 to 3.8.

https://github.com/IBM/differential-privacy-library