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Adversarial Machine Learning - examples of offensive and defensive techniques

ghcr.io/victorazzam/aml

GPL-3.0 license

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Dockerfile		Dockerfile
Guide.pdf		Guide.pdf
LICENSE.txt		LICENSE.txt
README.md		README.md
jupyter_notebook_config.py		jupyter_notebook_config.py
notebooks-EXTRACT-FIRST.tar.gz		notebooks-EXTRACT-FIRST.tar.gz
requirements.txt		requirements.txt

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Adversarial Machine Learning

Offensive and defensive examples.

Contents

Code examples
Jupyter notebooks (extract using tar xf notebooks-EXTRACT-FIRST.tar.gz)
Docker pre-built image
PDF walkthrough guide
Sources and extra links

Please refer to the PDF for guidance.

The dataset for the first defensive notebook is given in notebooks/defensive/1/dataset.txt as a link.

The last section titled Debugging concerns missing package issues. (Not all notebooks are meant to run by default, due to package incompatibility. If you wish to install them manually, run !pip install package_name in any notebook inside the container via the Jupyter Notebook web interface.)