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Irina NicolaeIrina Nicolae
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Fix naming in project info
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CONTRIBUTING.md

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# Contributing to Nemesis
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# Contributing to the Adversarial Robustness Toolbox
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Adding new features, improving documentation, fixing bugs, or writing tutorials are all examples of helpful contributions. Furthermore, if you are publishing a new attack or defense, we strongly encourage you to add it to Adversarial Robustness Toolbox so that others may evaluate it fairly in their own work.
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Adding new features, improving documentation, fixing bugs, or writing tutorials are all examples of helpful contributions. Furthermore, if you are publishing a new attack or defense, we strongly encourage you to add it to the Adversarial Robustness Toolbox so that others may evaluate it fairly in their own work.
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Bug fixes can be initiated through Github pull requests. When making code contributions to Adversarial Robustness Toolbox, we ask that you follow the `PEP 8` coding standard and that you provide unit tests for the new features.
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Bug fixes can be initiated through GitHub pull requests. When making code contributions to the Adversarial Robustness Toolbox, we ask that you follow the `PEP 8` coding standard and that you provide unit tests for the new features.
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README.md

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# Adversarial Robustness Toolbox (ART v0.3.0)
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[![Build Status](https://travis-ci.org/IBM/adversarial-robustness-toolbox.svg?branch=master)](https://travis-ci.org/IBM/adversarial-robustness-toolbox) [![GitHub version](https://badge.fury.io/gh/IBM%2Fadversarial-robustness-toolbox.svg)](https://badge.fury.io/gh/IBM%2Fadversarial-robustness-toolbox) [![Documentation Status](https://readthedocs.org/projects/adversarial-robustness-toolbox/badge/?version=latest)](http://adversarial-robustness-toolbox.readthedocs.io/en/latest/?badge=latest)
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[![Build Status](https://travis-ci.org/IBM/adversarial-robustness-toolbox.svg?branch=master)](https://travis-ci.org/IBM/adversarial-robustness-toolbox) [![Documentation Status](https://readthedocs.org/projects/adversarial-robustness-toolbox/badge/?version=latest)](http://adversarial-robustness-toolbox.readthedocs.io/en/latest/?badge=latest) [![GitHub version](https://badge.fury.io/gh/IBM%2Fadversarial-robustness-toolbox.svg)](https://badge.fury.io/gh/IBM%2Fadversarial-robustness-toolbox)
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This is a library dedicated to **adversarial machine learning**. Its purpose is to allow rapid crafting and analysis of attacks and defense methods for machine learning models. The Adversarial Robustness Toolbox provides an implementation for many state-of-the-art methods for attacking and defending classifiers.
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