Adversarial-Deep-Learning/code-soup
This is a collection of algorithms and approaches used in the book adversarial deep learning
This project provides Python code implementations for algorithms discussed in the book "Adversarial Deep Learning." It helps researchers and students understand how deep neural networks can be attacked and defended. You input conceptual algorithms from the book and get working code examples, allowing you to experiment with adversarial attacks and defenses. This is for anyone studying or working in the field of adversarial machine learning.
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Use this if you are reading the book "Adversarial Deep Learning" and want to see practical, runnable code implementations of the concepts and algorithms discussed.
Not ideal if you are looking for a high-level library to apply pre-built adversarial attacks or defenses without diving into the underlying algorithm implementations.
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17
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18
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Jan 16, 2022
Commits (30d)
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