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Update README.md to include additional information about HEART
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README.md
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license: mit
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---
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license: mit
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---
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# Hardened Extension of the Adversarial Robustness Toolbox (HEART)
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HEART is a Python extension library for Machine Learning Security that builds on the popular Adversarial Robustness algorithms within the [Adversarial Robustness Toolbox (ART)](https://github.com/Trusted-AI/adversarial-robustness-toolbox). The extension library allows the user to leverage core ART algorithms while providing additional benefits to AI Test & Evaluation (T&E) engineers.
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- Support for T&E of models for Department of Defense use cases
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- Alignment to [MAITE](https://github.com/mit-ll-ai-technology/maite) protocols for seamless T&E workflows
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- Essential subset of adversarial robustness methods for targeted AI security coverage
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- Quality assurance of model assessments in the form of metadata
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- In-depth support for users based on codified T&E expert experience in form of guides and examples
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- Front-end application for low-code users: HEART Gradio Application
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# Installation
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### From Python Packaging Index (PyPI)
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To install the latest version of HEART from PyPI, run:
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```shell
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pip install heart-library
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```
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### From IBM GitHub Source
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To install the latest version of HEART from the [heart-library public GitHub](https://github.com/IBM/heart-library), run:
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```shell
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git clone https://github.com/IBM/heart-library.git
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cd heart-library
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pip install .
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```
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### (Optional) Development Environment via Poetry
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In some cases, it may be beneficial for developers to set up an environment from a reproducible source of truth. This environment is useful for developers that wish to work within a pull request or leverage the same development conditions used by HEART contributors. Please follow the instructions for installation via Poetry within the official HEART repository:
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- [Poetry Installation Instructions](https://github.com/IBM/heart-library/blob/main/poetry_installation.md)
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# Getting Started With HEART
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IBM has published a catalog of notebooks designed to assist developers of all skill levels with the process of getting started utilizing HEART in their AI T&E workflows. These Jupyter notebooks can be accessed within the official heart-library GitHub repository:
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- [HEART Jupyter Notebooks](https://github.com/IBM/heart-library/tree/main/notebooks)
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# HEART Modules
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The HEART library is organized into three primary modules: attacks, estimators, and metrics.
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### heart_library.attacks
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> The HEART attacks module contains implementations of attack algorithms for generating adversarial examples and evaluating model robustness.
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### heart_library.estimators
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> The HEART estimators module contains classes that wrap and extend the evaluated model to make it compatible with attacks and metrics.
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### heart_library.metrics
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> The HEART metrics module implements industry standard, commonly-used T&E metrics for model evaluation.
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