dtox 0.1.0

TODO

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Intro
-----

**Detox** is an open source software library for machine learning
security. It contains tools for adversarial example generation and
provides a framework for building new types of attack methods.

Currently in the dev stage.

Attacks
-------

Available attack algorithms implemented in Detox:

- Fast Gradient Methods (FGM/FGSM)
```Tutorial`` </tutorial/source/fgsm.ipynb>`__
- Basic Iterative
```Tutorial`` </tutorial/source/basic_iterative.ipynb>`__
- Momentum Iterative
```Tutorial`` </tutorial/source/momentum_iterative.ipynb>`__
- DeepFool
- Universal Adversarial Perturbation (UAP)
- Jacobian-based Saliency Map Approach (JSMA)
- One Pixel Attack
- LBFGS
- Carlini Wagner L2
- Carlini Wagner L-inf
- Feature Adversaries
- Boundary Attack
- Elastic Net
- Natural Adversarial Examples (NAE)

The Team
~~~~~~~~

Detox is a community driven project. The project was initiated by
machine learning security team @ `KakaoBrain <kakaobrain.com>`__.

.. |license| image:: https://img.shields.io/github/license/mashape/apistatus.svg